Python Plot.plot_in_2d Examples

Example #1

File: gaussian_mixture_model.py Project: cpt-r3tr0/Scratch-ML

def main():
    # Load the dataset
    X, y = datasets.make_blobs()

    # Cluster the data
    clf = GaussianMixtureModel(k=3)
    y_pred = clf.predict(X)

    p = Plot()
    p.plot_in_2d(X, y_pred, title="GMM Clustering")
    p.plot_in_2d(X, y, title="Actual Clustering")

Example #2

File: k_means.py Project: cpt-r3tr0/Scratch-ML

def main():
    # Load the dataset
    X, y = datasets.make_blobs()

    # Cluster the data using K-Means
    clf = KMeans(k=3)
    y_pred = clf.predict(X)

    # Project the data onto the 2 primary principal components
    p = Plot()
    p.plot_in_2d(X, y_pred, title="K-Means Clustering")
    p.plot_in_2d(X, y, title="Actual Clustering")

Example #3

def main():
    # Load the dataset
    X, y = datasets.make_moons(n_samples=300, noise=0.08, shuffle=False)

    # Cluster the data using DBSCAN
    clf = DBSCAN(eps=0.17, min_samples=5)
    y_pred = clf.predict(X)

    # Project the data onto the 2 primary principal components
    p = Plot()
    p.plot_in_2d(X, y_pred, title="DBSCAN")
    p.plot_in_2d(X, y, title="Actual Clustering")