How to Choose a classification algorithm for particular problem?

By Rama, 6 months ago
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Explain how to choose an appropriate classification algorithm for a particular problem task.

Classification algorithm
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Choosing an appropriate classification algorithm for a particular problem task requires practice: each algorithm has its own features and is based on certain assumptions.

In practice, it is always recommended that you compare the performance of at least a handful of different learning algorithms to select the best model for the particular problem. These may differ in the number of features or samples, the amount of noise in a dataset, and whether the classes are linearly separable or not.

Eventually, the performance of a classifier, computational power as well as predictive power, depends heavily on the underlying data that are available for learning.

The five main steps that are involved in training a machine learning algorithm can be summarized as follows:

  1. Selection of features.
  2. Choosing a performance metric.
  3. Choosing a classifier and optimization algorithm.
  4. Evaluating the performance of the model.
  5. Tuning the algorithm.

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