def quickDemo():
    trials = 5000
    X, y = cl.makeData(train)
    index = rn.sample(range(0, 39739), trials)
    smallX = np.empty((trials, len(X[0])))
    smally = np.empty(trials, dtype='|S30')
    count = 0
    for i in index:
        smallX[count] = X[i]
        smally[count] = y[i]
        count = count + 1
    start = time.time()
    cl.SVM(smallX, smally)
    print((time.time() - start) / 5)
    start = time.time()
    cl.NearestNeighbor(smallX, smally)
    print((time.time() - start) / 5)
    start = time.time()
    cl.MLP(smallX, smally)
    print((time.time() - start) / 5)
def runFullTests():
    X, y = cl.makeData(train)

    cl.SVM(X, y)
    cl.NearestNeighbor(X, y)
    cl.MLP(X, y)
Esempio n. 3
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import Data
import Classifiers

samples = 5000
noise = 25

trainingData, trainingLabels, testData, testLabels = Data.createData(
    samples, noise)

Classifiers.MLP(trainingData, trainingLabels, testData, testLabels)

Classifiers.radialBF(trainingData, trainingLabels, testData, testLabels)

Classifiers.SVM(trainingData, trainingLabels, testData, testLabels)

Classifiers.RF(trainingData, trainingLabels, testData, testLabels)