{"cells": [{"metadata": {"button": false, "id": "d8386db0-6f9a-45ae-af2c-c55ad12f934b", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "markdown", "source": "\n\n

IBM-AWS Immersion Day Lab 4

Notebook 3 : Risk Index Prediction with Decision Tree

"}, {"metadata": {"button": false, "id": "6f47a209-6f2e-424e-8b4f-02165d0709fa", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "markdown", "source": "In this lab exercise, you will learn a popular machine learning algorithm, Decision Tree. You will use this classification algorithm to build a model from historical data of region and their total cases. Then you use the trained decision tree to predict the Risk Index of a region."}, {"metadata": {"button": false, "id": "15d643e2-8936-4d08-aa08-d6edee47d0c5", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "markdown", "source": "### Import required libraries"}, {"metadata": {"button": false, "id": "3274f764-7be0-4748-be5b-cf567a98a7a5", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "code", "source": "import numpy as np \nimport pandas as pd\nfrom sklearn.tree import DecisionTreeClassifier", "execution_count": 1, "outputs": []}, {"metadata": {"button": false, "id": "274a692a-b847-4faf-b59d-4b9038d4ea6b", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "markdown", "source": "### Load the dataset from Amazon S3 into pandas dataframe\n\n>Note: you can add the comment `# @hidden_cell` in the below code cell. Cloud Pak for Data will automatically hide the cell before sharing it."}, {"metadata": {"id": "afcc08f5b30d45ce94af85ee374db75b"}, "cell_type": "code", "source": "", "execution_count": 2, "outputs": [{"output_type": "execute_result", "execution_count": 2, "data": {"text/plain": " DATE REGION Total_cases Risk_Index\n0 2020-03-15 Brussels 119 0\n1 2020-03-15 Flanders 461 2\n2 2020-03-15 Wallonia 383 1\n3 2020-03-16 Brussels 238 0\n4 2020-03-16 Flanders 794 2\n5 2020-03-16 Wallonia 568 1\n6 2020-03-17 Brussels 219 0\n7 2020-03-17 Flanders 1414 2\n8 2020-03-17 Wallonia 654 1\n9 2020-03-18 Brussels 346 0", "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
DATEREGIONTotal_casesRisk_Index
02020-03-15Brussels1190
12020-03-15Flanders4612
22020-03-15Wallonia3831
32020-03-16Brussels2380
42020-03-16Flanders7942
52020-03-16Wallonia5681
62020-03-17Brussels2190
72020-03-17Flanders14142
82020-03-17Wallonia6541
92020-03-18Brussels3460
\n
"}, "metadata": {}}]}, {"metadata": {"button": false, "id": "9f0ee40d-3061-4602-a446-cc7f36005561", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "code", "source": "my_data = data_df_1", "execution_count": 3, "outputs": []}, {"metadata": {"button": false, "id": "b2b59ac4-c19b-48c5-baed-67e6da1db61b", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "markdown", "source": "#### Size of the Data"}, {"metadata": {"button": false, "id": "26ecd4a2-63b8-4e1d-bc31-50f075167878", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "code", "source": "my_data.shape", "execution_count": 4, "outputs": [{"output_type": "execute_result", "execution_count": 4, "data": {"text/plain": "(2220, 4)"}, "metadata": {}}]}, {"metadata": {"id": "70d4a16f-098f-460d-9e45-b52286d29a4b"}, "cell_type": "markdown", "source": "
\n

Data Pre-processing

\n
"}, {"metadata": {"button": false, "id": "d7d5db06-4627-4428-b79c-ee8424f80247", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "markdown", "source": "Using my_data read by pandas, declare the following variables:
\n\n"}, {"metadata": {"button": false, "id": "caef83bb-97ad-4949-a88b-25f4954d93bc", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "markdown", "source": "Remove the column containing the target name since it doesn't contain numeric values."}, {"metadata": {"id": "cc52705b-0a84-4fc3-94c8-606728c7c433"}, "cell_type": "code", "source": "X = my_data[['REGION', 'Total_cases']].values\nX[0:5]", "execution_count": 5, "outputs": [{"output_type": "execute_result", "execution_count": 5, "data": {"text/plain": "array([['Brussels', 119],\n ['Flanders', 461],\n ['Wallonia', 383],\n ['Brussels', 238],\n ['Flanders', 794]], dtype=object)"}, "metadata": {}}]}, {"metadata": {"id": "7a9e7082-91bd-4bff-8f6b-63cd7ea32080"}, "cell_type": "markdown", "source": "As you may figure out, some features in this dataset are categorical such as __Brussels__ or __Wallonia__ or __Flanders__. Unfortunately, Sklearn Decision Trees do not handle categorical variables. But still we can convert these features to numerical values. __pandas.get_dummies()__\nConvert categorical variable into dummy/indicator variables."}, {"metadata": {"id": "ba760599-1c90-44ce-9941-781afa2c4c22"}, "cell_type": "code", "source": "from sklearn import preprocessing\nle_region = preprocessing.LabelEncoder()\nle_region.fit(['Brussels','Flanders', 'Wallonia'])\nX[:,0] = le_region.transform(X[:,0]) \n\nX[0:5]", "execution_count": 6, "outputs": [{"output_type": "execute_result", "execution_count": 6, "data": {"text/plain": "array([[0, 119],\n [1, 461],\n [2, 383],\n [0, 238],\n [1, 794]], dtype=object)"}, "metadata": {}}]}, {"metadata": {"id": "1cecc9fa-7c95-4922-9057-a88f01fb7b3d"}, "cell_type": "markdown", "source": "Now we can fill the target variable."}, {"metadata": {"button": false, "id": "348f4912-7cb1-4e84-98c6-8e6374c50591", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "code", "source": "y = my_data[\"Risk_Index\"]\ny[0:5]", "execution_count": 7, "outputs": [{"output_type": "execute_result", "execution_count": 7, "data": {"text/plain": "0 0\n1 2\n2 1\n3 0\n4 2\nName: Risk_Index, dtype: int32"}, "metadata": {}}]}, {"metadata": {"button": false, "id": "47439b7a-79b2-48df-a20f-33e85deb5729", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "markdown", "source": "
\n\n
\n

Setting up the Decision Tree

\n We will be using train/test split on our decision tree. Let's import train_test_split from sklearn.cross_validation.\n
"}, {"metadata": {"button": false, "id": "08ad05ed-bddc-4703-8376-52a6b71bd115", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "code", "source": "from sklearn.model_selection import train_test_split", "execution_count": 8, "outputs": []}, {"metadata": {"button": false, "id": "2ad33c33-3458-4db4-b209-9245007e5ed1", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "markdown", "source": "Now train_test_split will return 4 different parameters. We will name them:
\nX_trainset, X_testset, y_trainset, y_testset

\nThe train_test_split will need the parameters:
\nX, y, test_size=0.3, and random_state=3.

\nThe X and y are the arrays required before the split, the test_size represents the ratio of the testing dataset, and the random_state ensures that we obtain the same splits."}, {"metadata": {"button": false, "id": "031e8d4a-a85f-4baa-ae1d-156fc6061fbd", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "code", "source": "X_trainset, X_testset, y_trainset, y_testset = train_test_split(X, y, test_size=0.3, random_state=3)", "execution_count": 9, "outputs": []}, {"metadata": {"button": false, "id": "27aa45a6-5d17-4ac9-880e-dc38416a9962", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "code", "source": "print(X_trainset.shape, y_trainset.shape, sep=\"\\n\")", "execution_count": 10, "outputs": [{"output_type": "stream", "text": "(1554, 2)\n(1554,)\n", "name": "stdout"}]}, {"metadata": {"button": false, "id": "909b8b54-e06b-4350-ac56-f7f39c0f9580", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "code", "source": "print(X_testset.shape, y_testset.shape, sep=\"\\n\")", "execution_count": 11, "outputs": [{"output_type": "stream", "text": "(666, 2)\n(666,)\n", "name": "stdout"}]}, {"metadata": {"button": false, "id": "fc0ab56e-1065-45e7-8bff-92b88ca67a9f", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "markdown", "source": "
\n\n
\n

Modeling

\n We will first create an instance of the DecisionTreeClassifier called riskIndexTree.
\n Inside of the classifier, specify criterion=\"entropy\" so we can see the information gain of each node.\n
"}, {"metadata": {"button": false, "id": "68ac91f5-9ab0-43fb-92f4-94d9c99a5ac0", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "code", "source": "riskIndexTree = DecisionTreeClassifier(criterion=\"entropy\", max_depth = 4)\nriskIndexTree", "execution_count": 12, "outputs": [{"output_type": "execute_result", "execution_count": 12, "data": {"text/plain": "DecisionTreeClassifier(criterion='entropy', max_depth=4)"}, "metadata": {}}]}, {"metadata": {"button": false, "id": "c7b1db09-630d-4375-a048-40a482450dc6", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "markdown", "source": "Next, we will fit the data with the training feature matrix X_trainset and training response vector y_trainset "}, {"metadata": {"button": false, "id": "da434a28-75ac-4c9c-b22d-06058af47000", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "code", "source": "riskIndexTree.fit(X_trainset,y_trainset)", "execution_count": 13, "outputs": [{"output_type": "execute_result", "execution_count": 13, "data": {"text/plain": "DecisionTreeClassifier(criterion='entropy', max_depth=4)"}, "metadata": {}}]}, {"metadata": {"button": false, "id": "04516e2e-b81a-4a15-9131-ce252e732e97", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "markdown", "source": "
\n\n
\n

Prediction

\n Let's make some predictions on the testing dataset and store it into a variable called predTree.\n
"}, {"metadata": {"button": false, "id": "10473bbf-c17c-4725-bd3c-0df8ac76579b", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "code", "source": "predTree = riskIndexTree.predict(X_testset)", "execution_count": 14, "outputs": []}, {"metadata": {"button": false, "id": "8aeffbaf-2a2d-49b4-9270-7b079de3c30e", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "markdown", "source": "You can print out predTree and y_testset if you want to visually compare the prediction to the actual values."}, {"metadata": {"button": false, "id": "2e161903-a0ae-4a02-b25e-6f5d5b4e8373", "new_sheet": false, "run_control": {"read_only": false}, "scrolled": true}, "cell_type": "code", "source": "print (predTree [0:5])\nprint (y_testset [0:5])", "execution_count": 15, "outputs": [{"output_type": "stream", "text": "[1 1 0 1 2]\n1821 1\n1830 1\n1903 0\n1452 1\n175 2\nName: Risk_Index, dtype: int32\n", "name": "stdout"}]}, {"metadata": {"button": false, "id": "ead57e9d-3018-4922-9bc4-23c580995953", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "markdown", "source": "
\n\n
\n

Evaluation

\n Next, let's import metrics from sklearn and check the accuracy of our model.\n
"}, {"metadata": {"button": false, "id": "daf4c906-f6bb-437d-a59c-ab2aeb783894", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "code", "source": "from sklearn import metrics\nimport matplotlib.pyplot as plt\nprint(\"DecisionTrees's Accuracy: \", metrics.accuracy_score(y_testset, predTree))", "execution_count": 16, "outputs": [{"output_type": "stream", "text": "DecisionTrees's Accuracy: 0.8618618618618619\n", "name": "stdout"}]}, {"metadata": {"button": false, "id": "09e26483-87fa-4945-9b87-620b4c297890", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "markdown", "source": "__Accuracy classification score__ computes subset accuracy: the set of labels predicted for a sample must exactly match the corresponding set of labels in y_true. \n\nIn multilabel classification, the function returns the subset accuracy. If the entire set of predicted labels for a sample strictly match with the true set of labels, then the subset accuracy is 1.0; otherwise it is 0.0.\n"}, {"metadata": {"id": "0deb6990-956f-40c7-8d75-851def88ef96"}, "cell_type": "markdown", "source": "
\n\n
\n

Visualization

\n Lets visualize the tree\n
"}, {"metadata": {"button": false, "id": "d132b478-6a45-4988-89d9-f0a0ed67d575", "new_sheet": false, "run_control": {"read_only": false}}, "cell_type": "code", "source": "from sklearn.tree import DecisionTreeRegressor\nfrom sklearn import tree", "execution_count": 17, "outputs": []}, {"metadata": {"id": "a93fdea4bf624b918b2660b0a8bb7221", "scrolled": false}, "cell_type": "code", "source": "fig = plt.figure(figsize=(25,20))\n_ = tree.plot_tree(riskIndexTree, feature_names=my_data.columns[0:5], filled=True)", "execution_count": 18, "outputs": [{"output_type": "display_data", "data": {"text/plain": "
", "image/png": 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\n"}, 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\n\nThe AutoAI graphical tool in Watson Studio analyzes your data and discovers data transformations, algorithms, and parameter settings that work best for your predictive modeling problem. AutoAI displays the results as model candidate pipelines ranked on a leaderboard for you to choose from.\n\nAlso, you can use Watson Studio to run these notebooks faster with bigger datasets. Watson Studio is IBM's leading cloud solution for data scientists, built by data scientists. With Jupyter notebooks, RStudio, Apache Spark and popular libraries pre-packaged in the cloud, Watson Studio enables data scientists to collaborate on their projects without having to install anything. Join the fast-growing community of Watson Studio users today with a free account at Watson Studio\n\n

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Author: Manoj Jahgirdar & Sharath Kumar RK

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