Created
April 15, 2017 10:05
-
-
Save QuantumDamage/09703d4980deab88a68672d34c600808 to your computer and use it in GitHub Desktop.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import numpy as np | |
from sklearn.model_selection import train_test_split | |
from xgboost import XGBClassifier | |
# NOTE: Make sure that the class is labeled 'class' in the data file | |
tpot_data = np.recfromcsv('PATH/TO/DATA/FILE', delimiter='COLUMN_SEPARATOR', dtype=np.float64) | |
features = np.delete(tpot_data.view(np.float64).reshape(tpot_data.size, -1), tpot_data.dtype.names.index('class'), axis=1) | |
training_features, testing_features, training_classes, testing_classes = \ | |
train_test_split(features, tpot_data['class'], random_state=42) | |
exported_pipeline = XGBClassifier(learning_rate=0.01, max_depth=6, min_child_weight=2, n_estimators=100, nthread=1, subsample=0.55) | |
exported_pipeline.fit(training_features, training_classes) | |
results = exported_pipeline.predict(testing_features) |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment