hw3-p3.py

from sklearn import svm, datasets
from sklearn.model_selection import StratifiedKFold
from sklearn.metrics import confusion_matrix, classification_report, RocCurveDisplay, ConfusionMatrixDisplay, auc

# Import some data to play with
iris = datasets.load_iris()
X = iris.data
y = iris.target
target_names = iris.target_names[:2]

X, y = X[y != 2], y[y != 2]
n_samples, n_features = X.shape

# Add 'noisy' features to make problem harder
noise_val = 15
X += np.random.random(X.shape)*noise_val