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rasbtrasbt
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update parsing scripts (#43)
1 parent 8c54875 commit 22c3431

30 files changed

Lines changed: 139 additions & 252 deletions

‎.travis.yml‎

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install:
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- sudo apt-get update
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- source .travis/install_travis_env.sh
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before_script: # configure a headless display to test plot generation
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- "export DISPLAY=:99.0"
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- "sh -e /etc/init.d/xvfb start"
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- sleep 3 # give xvfb some time to start
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script:
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- bash .travis/run_travis_tests.sh
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#after_success:
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# - if [[ "${COVERAGE}" == "true" ]]; then coveralls; codecov; else echo "failed"; fi
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notifications:
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email:
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recipients:

‎code/.convert_notebook_to_script.py‎

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import argparse
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import os
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import subprocess
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import textwrap
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def convert(input_path, output_path):
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clean_content = []
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imports = []
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existing_imports = set()
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with open(path, 'r') as f:
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next(f)
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next(f)
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for line in f:
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line = line.rstrip(' ')
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if line.startswith(skip_lines_startwith):
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continue
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if line.startswith('import') or (
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'from' in line and 'import' in line):
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imports.append(line)
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if line.startswith('import ') or (
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'from ' in line and 'import ' in line):
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if 'from __future__ import print_function' in line:
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if line != imports[0]:
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imports.insert(0, line)
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else:
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if line.strip() not in existing_imports:
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imports.append(line)
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existing_imports.add(line.strip())
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else:
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clean_content.append(line)
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‎code/ch02/ch02.ipynb‎

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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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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{

‎code/ch02/ch02.py‎

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import numpy as np
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import pandas as pd
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import matplotlib.pyplot as plt
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import numpy as np
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from matplotlib.colors import ListedColormap
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# *Python Machine Learning 2nd Edition* by [Sebastian Raschka](https://sebastianraschka.com), Packt Publishing Ltd. 2017

‎code/ch03/ch03.ipynb‎

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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"source": [
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"! python ../.convert_notebook_to_script.py --input ch03.ipynb --output ch03.py"
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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": {

‎code/ch03/ch03.py‎

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from sklearn.metrics import accuracy_score
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from matplotlib.colors import ListedColormap
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import matplotlib.pyplot as plt
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import matplotlib.pyplot as plt
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import numpy as np
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from sklearn.linear_model import LogisticRegression
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from sklearn.svm import SVC
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from sklearn.linear_model import SGDClassifier
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import matplotlib.pyplot as plt
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import numpy as np
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from sklearn.svm import SVC
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import matplotlib.pyplot as plt
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import numpy as np
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from sklearn.tree import DecisionTreeClassifier
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from pydotplus import graph_from_dot_data
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from sklearn.tree import export_graphviz

‎code/ch03/tree.png‎

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‎code/ch04/ch04.ipynb‎

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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{

‎code/ch04/ch04.py‎

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from io import StringIO
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import sys
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from sklearn.preprocessing import Imputer
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import pandas as pd
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import numpy as np
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from sklearn.preprocessing import LabelEncoder
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from sklearn.preprocessing import OneHotEncoder
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from sklearn.model_selection import train_test_split
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from sklearn.preprocessing import MinMaxScaler
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from sklearn.preprocessing import StandardScaler
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from sklearn.linear_model import LogisticRegression
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from sklearn.linear_model import LogisticRegression
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import matplotlib.pyplot as plt
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from sklearn.base import clone
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from itertools import combinations
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import numpy as np
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from sklearn.metrics import accuracy_score
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from sklearn.model_selection import train_test_split
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import matplotlib.pyplot as plt
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from sklearn.neighbors import KNeighborsClassifier
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from sklearn.ensemble import RandomForestClassifier
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importances = forest.feature_importances_
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from sklearn.feature_selection import SelectFromModel
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# *Python Machine Learning 2nd Edition* by [Sebastian Raschka](https://sebastianraschka.com), Packt Publishing Ltd. 2017
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random_state=1)
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forest.fit(X_train, y_train)
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importances = forest.feature_importances_
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indices = np.argsort(importances)[::-1]
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‎code/ch05/ch05.ipynb‎

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"output_type": "stream",
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"text": [
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"[NbConvertApp] Converting notebook ch05.ipynb to script\n",
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"[NbConvertApp] Writing 27719 bytes to ch05.py\n"
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"[NbConvertApp] Writing 27705 bytes to ch05.py\n"
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]
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}
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],

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