In this article, we will discuss various metrics of regression and classification in machine learning. We always think of steps involved in modeling a good machine learning algorithm. The one-step is the metrics for evaluation of the goodness of the model. When we fit our model and make a prediction, then we always try to know the error and the accuracy. This article will try to deliver and explain various error measurement methods in regression and classification.
Fully Explained SVM Classification with Python
There are criteria to evaluate the prediction quality of the model as shown below:
grid_search.GridSearchCV
and cross_validation.cross_val_score
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