MACHINE LEARNING WITH PYTHON: Step by Step methods to master Machine Learning with Python by Cane Alexander

MACHINE LEARNING WITH PYTHON: Step by Step methods to master Machine Learning with Python by Cane Alexander

Author:Cane, Alexander [Cane, Alexander]
Language: eng
Format: epub
Published: 2020-01-12T16:00:00+00:00


The attribute mean technique is used for replacing missing values with a mean/median value, so long as it is discrete, for specified database attributes. For example, in a database containing details of income for US families, if a family has an average income of X, you could use that value for replacing the same missing value in the other records.

Using Attribute Mean For All Same-Class Samples

We use this one for restricting calculations to one specified class. By doing this, we can get the value that applies to the row we are looking in for the mean/median of an attribute; that is calculated by searching all the database rows.

Let’s say, for example, that you have a database showing automobile prices, classifying them into ‘Low Budget,’ ‘Family,’ and ‘Luxury,’ among others. It would be more precise to replace missing values in the ‘Luxury’ prices with the average of all vehicles in that category, rather than the value obtained when you add in one or more of the other categories.

Predicting Probable Values Using Data Mining Algorithms



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