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Outliers

We all have heard of the idiom ‘odd one out ’  which means something unusual in comparison to the others in a group. Similarly, an outlier is an observation in a given dataset that lies far from the rest of the observations. That means an outlier is vastly larger or smaller than the remaining values…

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Data Preprocessing in Machine Learning

Data Preprocessing is a technique that is used to convert raw data into clean data. In other words, whenever the data is gathered from different sources, it is collected in raw format which is not feasible for the analysis. Therefore, certain steps are executed to convert the raw data into a clean dataset.  Importance of Data Pre-processing…

Why data normalization is important for non-linear classifiers
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Why data normalization is important for non-linear classifiers

The term “normalization” usually refers to the terms standardization and scaling. While standardization typically aims to rescale the data to have a mean of 0 and a standard deviation of 1, scaling focuses on changing the range of the values of the dataset.   As mentioned in [1] and in many other articles, data normalization…