April 2019
Beginner to intermediate
252 pages
4h 40m
English
Content preview from Machine Learning for Data Mining
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The linear regression model
Let's understand the linear regression model with the help of an example.
Consider the following:
In linear regression, every input predictor in the Input Layer is connected to the outcome field by a single connection weight, also known as the coefficient, and these coefficients are estimated by a single pass through the data. The number of coefficients will be equal to the number of predictors. This means that every predictor will have a coefficient associated with it.
Every input predictor is directly connected to the Target with a particular coefficient as its weight. So, we can easily see the impact of a one ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.