COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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all the data collected
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measure the accuracy of your model, create the model
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test the accuracy of your model
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learning new and different skills
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Detailed explanation-1: -Accuracy is defined as the percentage of correct predictions for the test data. It can be calculated easily by dividing the number of correct predictions by the number of total predictions.
Detailed explanation-2: -You can get the training set predictions as y train pred = clf. predict(X train) where clf is your fitted RandomForestClassifier . After that you can use metrics. accuracy score(y train, y train pred) to get the training accuracy.
Detailed explanation-3: -Training a model simply means learning (determining) good values for all the weights and the bias from labeled examples. In supervised learning, a machine learning algorithm builds a model by examining many examples and attempting to find a model that minimizes loss; this process is called empirical risk minimization.