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How to feed numeric data into a classifier?


How to feed numeric data into a classifier?

By : user2957108
Date : November 23 2020, 01:01 AM
I hope this helps you . From the doc:
code :
data = np.array([x[0] for x in data])
target = np.array([x[1] for x in data])


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Weka J48 Classifier: Cannot handle numeric class?

Weka J48 Classifier: Cannot handle numeric class?


By : Romain
Date : March 29 2020, 07:55 AM
I hope this helps you . I'm now trying to build a J48 (C4.5) classifier model on my training data using Weka. , The word vectors could be converted to binary like this:
how to access the python scikit learning code for Random Forest Classifier, Ada Boost Classifier, Extra Trees Classifier

how to access the python scikit learning code for Random Forest Classifier, Ada Boost Classifier, Extra Trees Classifier


By : Milan Knežević
Date : March 29 2020, 07:55 AM
will help you Check out this link for instructions on how to get the latest sources from git-hub. It is open source, so there is no issue getting the source. Like this:
code :
git clone git://github.com/scikit-learn/scikit-learn.git
How train a classifier on different feature types together? Like String,numeric,Categorical, timestamp etc

How train a classifier on different feature types together? Like String,numeric,Categorical, timestamp etc


By : PiiDish
Date : March 29 2020, 07:55 AM
this will help Many machine learning classifiers like logistic regression, random forest, decision trees and SVM work fine with both continuous and categorical features. My guess is that you have two paths to follow. The first one is data pre-processing. For example, convert all string/cateogorical data (name of a person) to integers or you can use ensemble learning.
Ensemble learning is when you combine different classifiers (each one dealing with one kind of heterogeneous feature) using majority vote, for example, so they can find a consensus in classification. Hope it helps.
Can I build a ML model with independent variables containing (time series+ categorical +numeric) and a classifier depend

Can I build a ML model with independent variables containing (time series+ categorical +numeric) and a classifier depend


By : user3566711
Date : March 29 2020, 07:55 AM
should help you out As most of the data are specific to the person; except expenditure time series, so it is better to bring time series data at person level. This can be done by feature engineering like:
As @cmxu suggested take various statistical measures. It will be even more beneficial to take these statistical measures at different time intervals like say mean at last 2 days, 5 days, 7 days, 15 days, 30 day, 90 days, 180 days etc.
Merging bag-of-words scikits classifier with arbitrary numeric fields

Merging bag-of-words scikits classifier with arbitrary numeric fields


By : bdgangel
Date : March 29 2020, 07:55 AM
I wish this helpful for you How would you merge a scikits-learn classifier that operates over a bag-of-words with one that operates on arbitrary numeric fields? , The easy way:
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