Spam Classifier

Spam Classifier is one of the basic project we do implementing Machine Learning. While building the projects there are some key points which we need to keep in mind:-

• Collect lots of data(Collect those word which occur frequently in spams)
• Take sophisticated features(which gives header in spam emails)
• Develop algorithms to process your input in different ways (recognizing misspellings in spam). Collect lots of data(Collect those word which occur frequently in spams)

One of the major thing in Machine Learning, after creating the model, we must know how to analys error:-

• Start with a simple algorithm, implement it quickly, and test it with your new training sets.
• Plot learning curves to decide if more data, more features, etc. are likely to help.
• Manually examine the errors on examples in the cross validation set and spotting the trend in error is also important thing in error analysis.

In the next blog, we will see Support Vector Machine.

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