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demo/guide-python/sklearn_examples.py

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+'''
+Created on 1 Apr 2015
+
+@author: Jamie Hall
+'''
+
+import sys
+sys.path.append('../../wrapper')
+import xgboost as xgb
+
+import numpy as np
+from sklearn.cross_validation import KFold
+from sklearn.grid_search import GridSearchCV
+from sklearn.metrics import confusion_matrix
+from sklearn.datasets import load_iris, load_digits, load_boston
+
+rng = np.random.RandomState(31337)
+
+
+print("Zeros and Ones from the Digits dataset: binary classification")
+digits = load_digits(2)
+y = digits['target']
+X = digits['data']
+kf = KFold(y.shape[0], n_folds=2, shuffle=True, random_state=rng)
+for train_index, test_index in kf:
+    xgb_model = xgb.XGBClassifier().fit(X[train_index],y[train_index])
+    predictions = xgb_model.predict(X[test_index])
+    actuals = y[test_index]
+    print(confusion_matrix(actuals, predictions))
+
+print("Iris: multiclass classification")
+iris = load_iris()
+y = iris['target']
+X = iris['data']
+kf = KFold(y.shape[0], n_folds=2, shuffle=True, random_state=rng)
+for train_index, test_index in kf:
+    xgb_model = xgb.XGBClassifier().fit(X[train_index],y[train_index])
+    predictions = xgb_model.predict(X[test_index])
+    actuals = y[test_index]
+    print(confusion_matrix(actuals, predictions))
+
+