Top "Classification" questions

In machine learning and statistics, classification is the problem of identifying which of a set of categories a new observation belongs to, on the basis of a training set of data containing observations whose category membership (label) is known.

A simple explanation of Naive Bayes Classification

I am finding it hard to understand the process of Naive Bayes, and I was wondering if someone could explain …

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Difference between classification and clustering in data mining?

Can someone explain what the difference is between classification and clustering in data mining? If you can, please give examples …

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What are advantages of Artificial Neural Networks over Support Vector Machines?

ANN (Artificial Neural Networks) and SVM (Support Vector Machines) are two popular strategies for supervised machine learning and classification. It's …

machine-learning neural-network classification svm
Save classifier to disk in scikit-learn

How do I save a trained Naive Bayes classifier to disk and use it to predict data? I have the …

python machine-learning scikit-learn classification
Scikit-learn train_test_split with indices

How do I get the original indices of the data when using train_test_split()? What I have is the …

python scipy scikit-learn classification
FailedPreconditionError: Attempting to use uninitialized in Tensorflow

I am working through the TensorFlow tutorial, which uses a "weird" format to upload the data. I would like to …

python pandas classification tensorflow
sklearn classifier get ValueError: bad input shape

I have a csv, struct is CAT1,CAT2,TITLE,URL,CONTENT, CAT1, CAT2, TITLE ,CONTENT are in chinese. I want …

python scikit-learn classification text-classification
How to interpret weka classification?

How can we interpret the classification result in weka using naive bayes? How is mean, std deviation, weight sum and …

classification weka
Error in eval(predvars, data, env) : object 'Rm' not found

dataset = read.csv('dataset/housing.header.binary.txt') dataset1 = dataset[6] #higest positive correlation dataset2 = dataset[13] #lowest negative correlation dependentVal= dataset[14] #…

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