Classifier Plots

Relevant Imports

In [1]:
from sklearn import svm
from sklearn.datasets import load_iris, load_breast_cancer

import sys

if '../' not in sys.path:
    sys.path.append('../')

Binary Labled Data - Breast Cancer Dataset

In [2]:
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);

Multiclass Labled Data - Iris Dataset

In [3]:
iris = load_iris()

iris_clf = svm.SVC(kernel='rbf',probability=True)
iris_clf.fit(iris.data[:,:2], iris.target);

Two Dimensional Classifier

In [4]:
from palantiri.ClassifierPlotHandlers import TwoDimensionalClassifierPlotHandler

plot_handler = TwoDimensionalClassifierPlotHandler(iris, iris_clf)
In [5]:
plot_handler.plot_prediction()
In [6]:
plot_handler.plot_roc()
In [7]:
plot_handler.plot_confusion_matrix()

Three Dimensional Classifier

In [8]:
from palantiri.ClassifierPlotHandlers import ThreeDimensionalClassifierPlotHandler

plot_handler = ThreeDimensionalClassifierPlotHandler(breast_cancer, breast_cancer_clf)
In [9]:
plot_handler.prediction_figure
In [10]:
plot_handler.plot_prediction()
In [11]:
plot_handler.plot_roc()
In [12]:
plot_handler.plot_confusion_matrix()
In [13]:
import pandas as pd
In [14]:
breast_cancer_df = pd.DataFrame(data=breast_cancer.data,columns=['x1','x2','x3'])
breast_cancer_df['target'] = breast_cancer.target
In [15]:
plot_handler_from_dataframe = ThreeDimensionalClassifierPlotHandler.from_pandas_dataframe(
    breast_cancer_df, breast_cancer_clf,class_names=['a','b'])
In [16]:
plot_handler_from_dataframe.plot_confusion_matrix()