Avishek Dutta asked . 2022-06-13

Naive Bayes

Being a beginner I am facing great confusion regarding the NaiveBayes classifier.

The examples I see are like this

O1 = NaiveBayes.fit(meas,species);
C1 = O1.predict(meas);
cMat1 = confusionmat(species,C1)

nbGau= NaiveBayes.fit(meas(:,1:2), species);
nbGauClass= nbGau.predict(meas(:,1:2));

Always the function is taking two inputs. My task is to compare different classification methods on IMU data. I have seven scenarios like walk, run, stairup etc. I have a sample data which is an extract of my full training data (extracted randomly from the plot by selecting 2 points) i.e. data of all 7 scenarios combined together.

Using classify(sample,training,group) I am getting good results. But for NaiveBayes I have no option to include this sample data as input.

AI, Data Science, and Statistics , Statistics and Machine Learning Toolbox , naivebayes , classif

Expert Answer

John Williams answered . 2024-12-21 16:08:54

"training" is used to train a classifier (pass it to FIT method), and "sample" is used to test the classifier performance on data not used for training (pass it to PREDICT method). for example:

O1 = NaiveBayes.fit(training,group);
C1 = O1.predict(sample);
cMat1 = confusionmat(sampleGroup,C1);

where sampleGroup is an array of true class labels for the predictor matrix in "sample".

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