from sklearn import svm
from sklearn.datasets import load_iris, load_breast_cancer
import sys
if '../' not in sys.path:
sys.path.append('../')
breast_cancer = load_breast_cancer()
breast_cancer_clf = svm.SVC(kernel='rbf',probability=True)
breast_cancer_clf.fit(breast_cancer.data[:, :3],breast_cancer.target);
iris = load_iris()
iris_clf = svm.SVC(kernel='rbf',probability=True)
iris_clf.fit(iris.data[:,:2], iris.target);
from palantiri.ClassifierPlotHandlers import TwoDimensionalClassifierPlotHandler
plot_handler = TwoDimensionalClassifierPlotHandler(iris, iris_clf)
plot_handler.plot_prediction()
plot_handler.plot_roc()
plot_handler.plot_confusion_matrix()
from palantiri.ClassifierPlotHandlers import ThreeDimensionalClassifierPlotHandler
plot_handler = ThreeDimensionalClassifierPlotHandler(breast_cancer, breast_cancer_clf)
plot_handler.prediction_figure
plot_handler.plot_prediction()
plot_handler.plot_roc()
plot_handler.plot_confusion_matrix()
import pandas as pd
breast_cancer_df = pd.DataFrame(data=breast_cancer.data,columns=['x1','x2','x3'])
breast_cancer_df['target'] = breast_cancer.target
plot_handler_from_dataframe = ThreeDimensionalClassifierPlotHandler.from_pandas_dataframe(
breast_cancer_df, breast_cancer_clf,class_names=['a','b'])
plot_handler_from_dataframe.plot_confusion_matrix()