![]() This relationship is actually a function which looks like: \[Y=f(x_\) and store the results in the pred variable pred <- predict(fit) During the training phase, we attempt to detect the relationship between the output (response) variable and the input variables (predictors). The training set is a part of the total data set. This data set is usually called training set and this phase of the process is called training phase. The machine learning process has three phases: The process of fitting a model on a data set that contains information about both independent and dependent variables. To build these models, advanced statistical analysis techniques are employed. In principle, machine learning develops models or algorithms that can predict an output value with an acceptable error margin, based on a set of known input values. ![]() Machine learning is a science that enables computer applications to learn without being explicitly programmed. ![]()
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