autotpot1.py

import tpot
pipeline_optimizer = tpot.TPOTClassifier(generations=5, #number of iterations to run the training
                                         population_size=20, #number of individuals to train
                                         cv=5) #number of folds in StratifiedKFold
pipeline_optimizer.fit(X_train, y_train) #fit the pipeline optimizer - can take a long time
print(pipeline_optimizer.score(X_test, y_test)) #print scoring for the pipeline
pipeline_optimizer.export('tpot_exported_pipeline.py') #export the pipeline - in Python code!