Class | Ai4r::Experiment::ClassifierEvaluator |
In: |
lib/ai4r/experiment/classifier_evaluator.rb
|
Parent: | Object |
The ClassifierEvaluator is useful to compare different classifiers algorithms. The evaluator builds the Classifiers using the same data examples, and provides methods to evalute their performance in parallel. It is a nice tool to compare and evaluate the performance of different algorithms, the same algorithm with different parameters, or your own new algorithm against the classic classifiers.
build_times | [R] | |
classifiers | [R] | |
eval_times | [R] |
Build all classifiers, using data examples found in data_set. The last attribute of each item is considered as the item class. Building times are measured by separate, and can be accessed through build_times attribute reader.
You can evaluate new data, predicting its class. e.g.
classifier.eval(['New York', '<30', 'F']) => ['Y', 'Y', 'Y', 'N', 'Y', 'Y', 'N']
Evaluation times are measured by separate, and can be accessed through eval_times attribute reader.
Test classifiers using a data set. The last attribute of each item is considered as the expected class. Data items are evaluated using all classifiers: evalution times, sucess rate, and quantity of classification errors are returned in a data set. The return data set has a row for every classifier tested, and the following attributes:
["Classifier", "Testing Time", "Errors", "Success rate"]