WEKA Tutorial #1.3 - How to Build a Data Mining Model from Scratch

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In this Part 3 video (of a 3 part series), we’re going to continue where we left off in the 2 previous episodes where I have shown you from installation of the WEKA software, to pre-processing the data set and model construction using the decision tree algorithm C4.5. In this video, I will show you how to interpret the decision rules obtained from the decision tree model. This 3 part video series is made for the absolute beginner as we guide you step-by-step on building a data mining model from scratch.

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In this specific example: is there a quick and easy way to reverse the effects of the standardization/normalization done prior to classification? My point is - a negative petalwidth is somewhat unpractical to classify irises on.

Beanez_VR
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can we take data from array express or GEO in weka? How do you know when to normalize or standardized.

richashrivastava
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Build a classification model for naturalgas price prediction dataset which is available on kaggle

Anjali-dpos
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does Weka deal with Sql server database ... ??

mustaphabaua
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What's the logic behind choosing split value of petal width as 0.79..?

abhipsatripathy
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