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Dealing with noisy data made easy : binning technique [data mining]
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Data binning in data mining is an important step of data pre processing to Dealing with noisy data and feature engineering python it is a way to group numbers of more or less continuous values into a smaller number of "bins".
The original data values are divided into small intervals known as bins and then they are replaced by a general value calculated for that bin.
Features are the term used for the columns in the analytics base table (ABT). There is a particular type of feature known as a continuous feature. These are features that have a very high cardinality because the allowed values (domain) is on a spectrum. We can convert these continuous features to categorical features through a process called binning.
we will see how to deal with noisy data using data binning
The original data values are divided into small intervals known as bins and then they are replaced by a general value calculated for that bin.
Features are the term used for the columns in the analytics base table (ABT). There is a particular type of feature known as a continuous feature. These are features that have a very high cardinality because the allowed values (domain) is on a spectrum. We can convert these continuous features to categorical features through a process called binning.
we will see how to deal with noisy data using data binning
Dealing with noisy data made easy : binning technique [data mining]
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