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Travis CI: Add pytest --doctest-modules machine_learning (#1016)

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* Travis CI: Add pytest --doctest-modules neural_network

Fixes #987
```
neural_network/perceptron.py:123: in <module>
    sample.insert(i, float(input('value: ')))
../lib/python3.7/site-packages/_pytest/capture.py:693: in read
    raise IOError("reading from stdin while output is captured")
E   OSError: reading from stdin while output is captured
-------------------------------------------------------------------------------- Captured stdout --------------------------------------------------------------------------------
('\nEpoch:\n', 399)
------------------------

value:
```

* Adding fix from #1056 -- thanks @QuantumNovice

* if __name__ == '__main__':

* pytest --ignore=virtualenv  # do not test our dependencies
This commit is contained in:
Christian Clauss
2019-08-10 22:48:00 +02:00
committed by GitHub
parent 91c3c98d2b
commit 36684db278
5 changed files with 16 additions and 135 deletions
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8
machine_learning/random_forest_classification/random_forest_classification.py
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@ -1,17 +1,19 @@
# Random Forest Classification
# Importing the libraries
import os
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# Importing the dataset
dataset = pd.read_csv('Social_Network_Ads.csv')
script_dir = os.path.dirname(os.path.realpath(__file__))
dataset = pd.read_csv(os.path.join(script_dir, 'Social_Network_Ads.csv'))
X = dataset.iloc[:, [2, 3]].values
y = dataset.iloc[:, 4].values
# Splitting the dataset into the Training set and Test set
from sklearn.cross_validation import train_test_split
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.25, random_state = 0)
# Feature Scaling
@ -66,4 +68,4 @@ plt.title('Random Forest Classification (Test set)')
plt.xlabel('Age')
plt.ylabel('Estimated Salary')
plt.legend()
plt.show()
plt.show()