Is the subprocess done?
Return a sample of the input data
Start as a detached subprocess, immediately returning execution to caller.
Confusion Matrix
A simpler version of ParamSearch without Wrapped Progressive Sampling
ParamSearch with support for Wrapped Progressive Sampling
Compute Area Under the Curve (AUC) using the trapezoidal rule
This is a general fuction, given points on a curve. For computing the area under the ROC-curve, see auc_score().
auc : float
>>> import numpy as np
>>> from sklearn import metrics
>>> y = np.array([1, 1, 2, 2])
>>> pred = np.array([0.1, 0.4, 0.35, 0.8])
>>> fpr, tpr, thresholds = metrics.roc_curve(y, pred, pos_label=2)
>>> metrics.auc(fpr, tpr)
0.75
auc_score : Computes the area under the ROC curve
Extract a training set, test set and optimally a development set from one file, or multiple interdependent files (such as a parallel corpus). It is assumed each line contains one instance (such as a word or sentence for example).