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

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@mariusberg7535 5 ай бұрын

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.

@richashrivastava3981 4 жыл бұрын

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

@DataProfessor 4 жыл бұрын

I haven’t tried those data, but if it is in csv then you can import it in (might also need to format it as .arff) Both normalize and standardize can be used to scale the data. I prefer to use standardize as it scales the data to zero mean and unit variance (sd=1)

@richashrivastava3981 4 жыл бұрын

@@DataProfessor if as a beginner in the field of data science how to start especially in biological data

@DataProfessor 4 жыл бұрын

@@richashrivastava3981 I would recommend to start learning Python as it will be central to learning data science. There's a great book on this for learning Python for biologists, amzn.to/30L1THv Also, I've written a Medium article laying out the roadmap on getting started in data science, please check it out here towardsdatascience.com/10-things-i-wish-i-knew-about-learning-data-science-7a30bfb91759 And here is my strategies for learning data science towardsdatascience.com/strategies-for-learning-data-science-47053b58c19f

@Anjali-dp4os 3 жыл бұрын

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

@abhipsatripathy3934 4 жыл бұрын

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

@DataProfessor 4 жыл бұрын

The split value is determined by the algorithm as the decision threshold that leads to a series of branches until a leaf node is reached that culminates in a decision of the final class label samples are classified as.