How to Choose a classification algorithm for particular problem?

By Rama, 6 months ago
  • Bookmark

Explain how to choose an appropriate classification algorithm for a particular problem task.

Classification algorithm
1 Answer

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.

Your Answer


More webinars

Related Discussions

Running random forest algorithm with one variable

View More
We're Online!

Chat now for any query