Which evaluation statement should you use?

HOTSPOT

You are using C-Support Vector classification to do a multi-class classification with an unbalanced training dataset.

The C-Support Vector classification using Python code shown below:

You need to evaluate the C-Support Vector classification code.

Which evaluation statement should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

View Answer

Answer:

Explanation:

Box 1: Automatically adjust weights inversely proportional to class frequencies in the input data

The “balanced” mode uses the values of y to automatically adjust weights inversely proportional to class frequencies in the input data as n_samples / (n_classes * np.bincount(y)).

Box 2: Penalty parameter

Parameter: C : float, optional (default=1.0)

Penalty parameter C of the error term.

References: https://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html