Choose the correct sequence for classifier building from the following.

a) Train-->Test-->Initialize-->Predict

b) Initialize-->Train-->Predict-->Evaluate

c) Initialize-->Evaluate-->Train-->Predict

d) None

b

Explanation:

First, we need to initialize the classifier.

Then, we are required to train the classifier.

The next step is to predict the target.

And finally, we need to evaluate the classifier model.

You will find different algorithms for solving the classification problem. Some of them are like decision tree classification etc.

However, you need to know how these classifier works. And its explained before:

You need to initialize the classifier at first.

All kinds of classifiers in the scikit-learn make use of the method fit (x, y) for fitting the model or the training for the given training set in level y.

The predict (x) returns the y which is the predicted label. And this is prediction.

For evaluating the classifier model - the score (x, y) gives back the certain score for a mentioned test data x as well as the test label y.