Add TensorFlow nearest neighbor notebook.
Donne Martin
parent
47c1483f46
commit
60ebead762
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@ -97,6 +97,7 @@ IPython Notebook(s) demonstrating deep learning functionality.
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| [tsf-basics](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/deep-learning/tensor-flow-examples/1_intro/basic_operations.ipynb) | Learn basic operations in TensorFlow, a library for various kinds of perceptual and language understanding tasks from Google. |
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| [tsf-linear](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/deep-learning/tensor-flow-examples/2_basic_classifiers/linear_regression.ipynb) | Implement linear regression in TensorFlow. |
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| [tsf-logistic](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/deep-learning/tensor-flow-examples/2_basic_classifiers/logistic_regression.ipynb) | Implement logistic regression in TensorFlow. |
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| [tsf-nn](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/deep-learning/tensor-flow-examples/2_basic_classifiers/nearest_neighbor.ipynb) | Implement nearest neighboars in TensorFlow. |
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### tensor-flow-exercises
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@ -0,0 +1,386 @@
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Nearest Neighbor in TensorFlow\n",
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"\n",
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"Credits: Forked from [TensorFlow-Examples](https://github.com/aymericdamien/TensorFlow-Examples) by Aymeric Damien\n",
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"\n",
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"## Setup\n",
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"\n",
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"Refer to the [setup instructions](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/deep-learning/tensor-flow-examples/Setup_TensorFlow.md)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import tensorflow as tf"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Extracting /tmp/data/train-images-idx3-ubyte.gz\n",
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"Extracting /tmp/data/train-labels-idx1-ubyte.gz\n",
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"Extracting /tmp/data/t10k-images-idx3-ubyte.gz\n",
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"Extracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
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]
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}
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],
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"source": [
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"# Import MINST data\n",
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"import input_data\n",
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"mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=True)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"# In this example, we limit mnist data\n",
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"Xtr, Ytr = mnist.train.next_batch(5000) #5000 for training (nn candidates)\n",
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"Xte, Yte = mnist.test.next_batch(200) #200 for testing"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"# Reshape images to 1D\n",
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"Xtr = np.reshape(Xtr, newshape=(-1, 28*28))\n",
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"Xte = np.reshape(Xte, newshape=(-1, 28*28))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"# tf Graph Input\n",
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"xtr = tf.placeholder(\"float\", [None, 784])\n",
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"xte = tf.placeholder(\"float\", [784])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"# Nearest Neighbor calculation using L1 Distance\n",
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"# Calculate L1 Distance\n",
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"distance = tf.reduce_sum(tf.abs(tf.add(xtr, tf.neg(xte))), reduction_indices=1)\n",
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"# Predict: Get min distance index (Nearest neighbor)\n",
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"pred = tf.arg_min(distance, 0)\n",
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"\n",
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"accuracy = 0."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"# Initializing the variables\n",
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"init = tf.initialize_all_variables()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Test 0 Prediction: 7 True Class: 7\n",
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"Test 1 Prediction: 2 True Class: 2\n",
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"Test 2 Prediction: 1 True Class: 1\n",
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"Test 3 Prediction: 0 True Class: 0\n",
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"Test 4 Prediction: 4 True Class: 4\n",
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"Test 5 Prediction: 1 True Class: 1\n",
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"Test 6 Prediction: 4 True Class: 4\n",
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"Test 7 Prediction: 9 True Class: 9\n",
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"Test 8 Prediction: 8 True Class: 5\n",
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"Test 9 Prediction: 9 True Class: 9\n",
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"Test 10 Prediction: 0 True Class: 0\n",
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"Test 11 Prediction: 0 True Class: 6\n",
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"Test 12 Prediction: 9 True Class: 9\n",
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"Test 13 Prediction: 0 True Class: 0\n",
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"Test 14 Prediction: 1 True Class: 1\n",
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"Test 15 Prediction: 5 True Class: 5\n",
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"Test 16 Prediction: 4 True Class: 9\n",
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"Test 17 Prediction: 7 True Class: 7\n",
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"Test 18 Prediction: 3 True Class: 3\n",
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"Test 19 Prediction: 4 True Class: 4\n",
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"Test 20 Prediction: 9 True Class: 9\n",
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"Test 21 Prediction: 6 True Class: 6\n",
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"Test 22 Prediction: 6 True Class: 6\n",
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"Test 23 Prediction: 5 True Class: 5\n",
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"Test 24 Prediction: 4 True Class: 4\n",
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"Test 25 Prediction: 0 True Class: 0\n",
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"Test 26 Prediction: 7 True Class: 7\n",
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"Test 27 Prediction: 4 True Class: 4\n",
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"Test 28 Prediction: 0 True Class: 0\n",
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"Test 29 Prediction: 1 True Class: 1\n",
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"Test 30 Prediction: 3 True Class: 3\n",
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"Test 31 Prediction: 1 True Class: 1\n",
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"Test 32 Prediction: 3 True Class: 3\n",
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"Test 33 Prediction: 4 True Class: 4\n",
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"Test 34 Prediction: 7 True Class: 7\n",
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"Test 35 Prediction: 2 True Class: 2\n",
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"Test 36 Prediction: 7 True Class: 7\n",
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"Test 37 Prediction: 1 True Class: 1\n",
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"Test 38 Prediction: 2 True Class: 2\n",
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"Test 39 Prediction: 1 True Class: 1\n",
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"Test 40 Prediction: 1 True Class: 1\n",
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"Test 41 Prediction: 7 True Class: 7\n",
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"Test 42 Prediction: 4 True Class: 4\n",
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"Test 43 Prediction: 1 True Class: 2\n",
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"Test 44 Prediction: 3 True Class: 3\n",
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"Test 45 Prediction: 5 True Class: 5\n",
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"Test 46 Prediction: 1 True Class: 1\n",
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"Test 47 Prediction: 2 True Class: 2\n",
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"Test 48 Prediction: 4 True Class: 4\n",
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"Test 49 Prediction: 4 True Class: 4\n",
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"Test 50 Prediction: 6 True Class: 6\n",
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"Test 51 Prediction: 3 True Class: 3\n",
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"Test 52 Prediction: 5 True Class: 5\n",
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"Test 53 Prediction: 5 True Class: 5\n",
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"Test 54 Prediction: 6 True Class: 6\n",
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"Test 55 Prediction: 0 True Class: 0\n",
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"Test 56 Prediction: 4 True Class: 4\n",
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"Test 57 Prediction: 1 True Class: 1\n",
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"Test 58 Prediction: 9 True Class: 9\n",
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"Test 59 Prediction: 5 True Class: 5\n",
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"Test 60 Prediction: 7 True Class: 7\n",
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"Test 61 Prediction: 8 True Class: 8\n",
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"Test 62 Prediction: 9 True Class: 9\n",
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"Test 63 Prediction: 3 True Class: 3\n",
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"Test 64 Prediction: 7 True Class: 7\n",
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"Test 65 Prediction: 4 True Class: 4\n",
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"Test 66 Prediction: 6 True Class: 6\n",
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"Test 67 Prediction: 4 True Class: 4\n",
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"Test 68 Prediction: 3 True Class: 3\n",
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"Test 69 Prediction: 0 True Class: 0\n",
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"Test 70 Prediction: 7 True Class: 7\n",
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"Test 71 Prediction: 0 True Class: 0\n",
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"Test 72 Prediction: 2 True Class: 2\n",
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"Test 73 Prediction: 7 True Class: 9\n",
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"Test 74 Prediction: 1 True Class: 1\n",
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"Test 75 Prediction: 7 True Class: 7\n",
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"Test 76 Prediction: 3 True Class: 3\n",
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"Test 77 Prediction: 7 True Class: 2\n",
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"Test 78 Prediction: 9 True Class: 9\n",
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"Test 79 Prediction: 7 True Class: 7\n",
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"Test 80 Prediction: 7 True Class: 7\n",
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"Test 81 Prediction: 6 True Class: 6\n",
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"Test 82 Prediction: 2 True Class: 2\n",
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"Test 83 Prediction: 7 True Class: 7\n",
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"Test 84 Prediction: 8 True Class: 8\n",
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"Test 85 Prediction: 4 True Class: 4\n",
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"Test 86 Prediction: 7 True Class: 7\n",
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"Test 87 Prediction: 3 True Class: 3\n",
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"Test 88 Prediction: 6 True Class: 6\n",
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"Test 89 Prediction: 1 True Class: 1\n",
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"Test 90 Prediction: 3 True Class: 3\n",
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"Test 91 Prediction: 6 True Class: 6\n",
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"Test 92 Prediction: 9 True Class: 9\n",
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"Test 93 Prediction: 3 True Class: 3\n",
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"Test 94 Prediction: 1 True Class: 1\n",
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"Test 95 Prediction: 4 True Class: 4\n",
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"Test 96 Prediction: 1 True Class: 1\n",
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"Test 97 Prediction: 7 True Class: 7\n",
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"Test 98 Prediction: 6 True Class: 6\n",
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"Test 99 Prediction: 9 True Class: 9\n",
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"Test 100 Prediction: 6 True Class: 6\n",
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"Test 101 Prediction: 0 True Class: 0\n",
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"Test 102 Prediction: 5 True Class: 5\n",
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"Test 103 Prediction: 4 True Class: 4\n",
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"Test 104 Prediction: 9 True Class: 9\n",
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"Test 105 Prediction: 9 True Class: 9\n",
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"Test 106 Prediction: 2 True Class: 2\n",
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"Test 107 Prediction: 1 True Class: 1\n",
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"Test 108 Prediction: 9 True Class: 9\n",
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"Test 109 Prediction: 4 True Class: 4\n",
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"Test 110 Prediction: 8 True Class: 8\n",
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"Test 111 Prediction: 7 True Class: 7\n",
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"Test 112 Prediction: 3 True Class: 3\n",
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"Test 113 Prediction: 9 True Class: 9\n",
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"Test 114 Prediction: 7 True Class: 7\n",
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"Test 115 Prediction: 9 True Class: 4\n",
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"Test 116 Prediction: 9 True Class: 4\n",
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"Test 117 Prediction: 4 True Class: 4\n",
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"Test 118 Prediction: 9 True Class: 9\n",
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"Test 119 Prediction: 7 True Class: 2\n",
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"Test 120 Prediction: 5 True Class: 5\n",
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"Test 121 Prediction: 4 True Class: 4\n",
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"Test 122 Prediction: 7 True Class: 7\n",
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"Test 123 Prediction: 6 True Class: 6\n",
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"Test 124 Prediction: 7 True Class: 7\n",
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"Test 125 Prediction: 9 True Class: 9\n",
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"Test 126 Prediction: 0 True Class: 0\n",
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"Test 127 Prediction: 5 True Class: 5\n",
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"Test 128 Prediction: 8 True Class: 8\n",
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"Test 129 Prediction: 5 True Class: 5\n",
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"Test 130 Prediction: 6 True Class: 6\n",
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"Test 131 Prediction: 6 True Class: 6\n",
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"Test 132 Prediction: 5 True Class: 5\n",
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"Test 133 Prediction: 7 True Class: 7\n",
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"Test 134 Prediction: 8 True Class: 8\n",
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"Test 135 Prediction: 1 True Class: 1\n",
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"Test 136 Prediction: 0 True Class: 0\n",
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"Test 137 Prediction: 1 True Class: 1\n",
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"Test 138 Prediction: 6 True Class: 6\n",
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"Test 139 Prediction: 4 True Class: 4\n",
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"Test 140 Prediction: 6 True Class: 6\n",
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"Test 141 Prediction: 7 True Class: 7\n",
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"Test 142 Prediction: 2 True Class: 3\n",
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"Test 143 Prediction: 1 True Class: 1\n",
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"Test 144 Prediction: 7 True Class: 7\n",
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"Test 145 Prediction: 1 True Class: 1\n",
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"Test 146 Prediction: 8 True Class: 8\n",
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"Test 147 Prediction: 2 True Class: 2\n",
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"Test 148 Prediction: 0 True Class: 0\n",
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"Test 149 Prediction: 1 True Class: 2\n",
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"Test 150 Prediction: 9 True Class: 9\n",
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"Test 151 Prediction: 9 True Class: 9\n",
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"Test 152 Prediction: 5 True Class: 5\n",
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"Test 153 Prediction: 5 True Class: 5\n",
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"Test 154 Prediction: 1 True Class: 1\n",
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"Test 155 Prediction: 5 True Class: 5\n",
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"Test 156 Prediction: 6 True Class: 6\n",
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"Test 157 Prediction: 0 True Class: 0\n",
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"Test 158 Prediction: 3 True Class: 3\n",
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"Test 159 Prediction: 4 True Class: 4\n",
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"Test 160 Prediction: 4 True Class: 4\n",
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"Test 161 Prediction: 6 True Class: 6\n",
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"Test 162 Prediction: 5 True Class: 5\n",
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"Test 163 Prediction: 4 True Class: 4\n",
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"Test 164 Prediction: 6 True Class: 6\n",
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"Test 165 Prediction: 5 True Class: 5\n",
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"Test 166 Prediction: 4 True Class: 4\n",
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"Test 167 Prediction: 5 True Class: 5\n",
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"Test 168 Prediction: 1 True Class: 1\n",
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"Test 169 Prediction: 4 True Class: 4\n",
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"Test 170 Prediction: 9 True Class: 4\n",
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"Test 171 Prediction: 7 True Class: 7\n",
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"Test 172 Prediction: 2 True Class: 2\n",
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"Test 173 Prediction: 3 True Class: 3\n",
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"Test 174 Prediction: 2 True Class: 2\n",
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"Test 175 Prediction: 1 True Class: 7\n",
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"Test 176 Prediction: 1 True Class: 1\n",
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"Test 177 Prediction: 8 True Class: 8\n",
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"Test 178 Prediction: 1 True Class: 1\n",
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"Test 179 Prediction: 8 True Class: 8\n",
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"Test 180 Prediction: 1 True Class: 1\n",
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"Test 181 Prediction: 8 True Class: 8\n",
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"Test 182 Prediction: 5 True Class: 5\n",
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"Test 183 Prediction: 0 True Class: 0\n",
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"Test 184 Prediction: 2 True Class: 8\n",
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"Test 185 Prediction: 9 True Class: 9\n",
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"Test 186 Prediction: 2 True Class: 2\n",
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"Test 187 Prediction: 5 True Class: 5\n",
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"Test 188 Prediction: 0 True Class: 0\n",
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"Test 189 Prediction: 1 True Class: 1\n",
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"Test 190 Prediction: 1 True Class: 1\n",
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"Test 191 Prediction: 1 True Class: 1\n",
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"Test 192 Prediction: 0 True Class: 0\n",
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"Test 193 Prediction: 4 True Class: 9\n",
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"Test 194 Prediction: 0 True Class: 0\n",
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"Test 195 Prediction: 1 True Class: 3\n",
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"Test 196 Prediction: 1 True Class: 1\n",
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"Test 197 Prediction: 6 True Class: 6\n",
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"Test 198 Prediction: 4 True Class: 4\n",
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"Test 199 Prediction: 2 True Class: 2\n",
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"Done!\n",
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"Accuracy: 0.92\n"
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]
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}
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],
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"source": [
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"# Launch the graph\n",
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"with tf.Session() as sess:\n",
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" sess.run(init)\n",
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"\n",
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" # loop over test data\n",
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" for i in range(len(Xte)):\n",
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" # Get nearest neighbor\n",
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" nn_index = sess.run(pred, feed_dict={xtr: Xtr, xte: Xte[i,:]})\n",
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" # Get nearest neighbor class label and compare it to its true label\n",
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" print \"Test\", i, \"Prediction:\", np.argmax(Ytr[nn_index]), \\\n",
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" \"True Class:\", np.argmax(Yte[i])\n",
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" # Calculate accuracy\n",
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" if np.argmax(Ytr[nn_index]) == np.argmax(Yte[i]):\n",
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" accuracy += 1./len(Xte)\n",
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" print \"Done!\"\n",
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" print \"Accuracy:\", accuracy"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.4.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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