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sasankaweera123/simpleMl.py

Created July 25, 2022 05:09
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  1. sasankaweera123 created this gist Jul 25, 2022.
    34 changes: 34 additions & 0 deletions simpleMl.py
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    from sklearn.linear_model import LinearRegression
    import random

    feature_set = []
    target_set = []

    nRows = 200
    randomNLimit = 2000

    for i in range(0, nRows):
    x = random.randint(0, randomNLimit)
    y = random.randint(0, randomNLimit)
    z = random.randint(0, randomNLimit)

    function = (10*x)+(2*y)+(3*z)

    feature_set.append([x, y, z])
    target_set.append(function)

    # Model

    model = LinearRegression()
    model.fit(feature_set, target_set)

    # Testing Data set
    test_set = [[8, 4, 7]] # Expected Output = function(8,4,7) = (10*8) + (2*4) + (3*7) = 109
    prediction = model.predict(test_set)

    test_set_2 = [[9, 2, 2]] # Expected Output = function(9,2,2) = (10*9) + (2*2) + (3*2) = 100
    prediction2 = model.predict(test_set_2)


    print('Prediction:' + str(prediction) + ' Co - Efficient: ' + str(model.coef_))
    print('Prediction:' + str(prediction2) + ' Co - Efficient: ' + str(model.coef_))