Tell us how will you know which machine learning algorithm to choose for your classification problem?

Submitted by: Muhammad
If accuracy is a major concern for you when deciding on a machine learning algorithm then the best way to go about it is test a couple of different ones (by trying different parameters within each algorithm ) and choose the best one by cross-validation. A general rule of thumb to choose a good enough machine learning algorithm for your classification problem is based on how large your training set is. If the training set is small then using low variance/high bias classifiers like Naïve Bayes is advantageous over high variance/low bias classifiers like k-nearest neighbour algorithms as it might overfit the model. High variance/low bias classifiers tend to win when the training set grows in size.
Submitted by: Muhammad

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