Weighted Voting Class Prediction

What would you like to do?

• Build and evaluate a classifier
• Evaluate an existing classifier
• Classify an unknown sample using an existing classifier

Build and evaluate a classifier

Build and evaluate class predictors (classifiers) using the weighted voting class prediction method. How many gene expression data sets do you have?

• Two data sets. Click here to build a classifier against one data set and evaluate it against the other.
• One large data set. If you have one large data set, use the SplitDatasetTrainTest module to split it into two data sets. Then, click here to build a classifier against one data set and evaluate it against the other.
• One data set. If you have one smaller data set that cannot easily be split, click here to build and evaluate classifiers using cross-validation.

Evaluate an existing classifier

To evaluate an existing weighted voting classifier, you must have built the classifier using the WeightedVoting module. Do you have a classifier (*.model) file?

• Yes. Click here to evaluate your existing classifier.
• No. Use the build and evaluate a classifier instructions above to build a classifier.

Classify an unknown sample using an existing classifier

To classify an unknown sample, you must have built a weighted voting classifier using the WeightedVoting module. Do you have a classifier (*.model) file?

• Yes. Click here to classify an unknown sample using your existing classifier.
• No. Use the build and evaluate a classifier instructions above to build a classifier.