My first attempt with Local Outlier Factor(LOF): Identifying Density Based Local Outliers

One of the challenges in data analysis in general and predictive modeling in particular is dealing with outliers. There are many modeling techniques which are resistant to outliers or reduce the impact of them, but still detecting outliers and understanding them can lead to interesting findings. In previous post I used one of the linear […]

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Data Preparation for Predictive Modeling: Resolving Skewness

Skewness is a measure of asymmetry of distribution. Many model building techniques have the assumption that predictor values are distributed normally and have a symmetrical shape. In this post we discuss data preparation methods for resolving skewness. Data preparation is a critical first step for building high performance predictive models. In a series of posts […]

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Data Preparation for Predictive Modeling: Centering & Scaling

Data preparation is a critical first step for building high performance predictive models. In a series of posts we discuss important data preparation techniques that improve the performance of predictive models. Below are techniques we are planning to cover in Data Preparation For Predictive Modeling Series: Centering & Scaling Resolving Skewness Resolving Outliers Data Reduction […]

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