Recipe: How to prepare a machine learning workflow in Python?
DATA MUNGING

How to prepare a machine learning workflow in Python?

This recipe helps you prepare a machine learning workflow in Python
In [2]:
## How to prepare a machine leaning workflow in Python 
def Kickstarter_Example_25():
    print()
    print(format('How to prepare a machine leaning workflow in Python', '*^82'))

    import warnings
    warnings.filterwarnings("ignore")

    # Load libraries
    from sklearn import datasets
    from sklearn.preprocessing import StandardScaler
    from sklearn.linear_model import Perceptron
    from sklearn.model_selection import train_test_split
    from sklearn.metrics import accuracy_score, confusion_matrix

    # Load the iris dataset
    iris = datasets.load_iris()

    # Create our X and y data
    X = iris.data
    y = iris.target

    # Split the data into 70% training data and 30% test data
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)

    # Preprocess The X Data By Scaling
    sc = StandardScaler(with_mean=True, with_std=True)
    sc.fit(X_train)

    # Apply the scaler to the X training data
    X_train_std = sc.transform(X_train)

    # Apply the SAME scaler to the X test data
    X_test_std = sc.transform(X_test)

    #Train A Perceptron Learner
    ppn = Perceptron(alpha=0.0001, class_weight=None, eta0=0.1,
                     fit_intercept=True, n_iter=40, n_jobs=4,
                     penalty=None, random_state=0, shuffle=True,
                     verbose=0, warm_start=False)

    # Train the perceptron
    ppn.fit(X_train_std, y_train)

    # Apply The Trained Learner To Test Data
    y_pred = ppn.predict(X_test_std)

    # Compare The Predicted Y With The True Y
    # View the predicted y test data
    print(); print("y_pred: ", y_pred)

    # View the true y test data
    print(); print("y_test: ", y_test)

    # Examine Accuracy Metric
    print(); print('Accuracy: %.2f' % accuracy_score(y_test, y_pred))
    print(); print('Comfusion Matrix:\n', confusion_matrix(y_test, y_pred))

Kickstarter_Example_25()
***************How to prepare a machine leaning workflow in Python****************

y_pred:  [1 1 1 1 2 0 0 1 2 0 1 1 1 1 1 1 2 0 1 1 0 1 0 1 2 1 2 1 0 1 0 2 1 0 1 0 1
 0 1 0 2 0 1 1 1]

y_test:  [2 2 2 1 2 0 0 2 2 0 2 1 2 1 1 2 2 0 1 1 0 1 0 1 2 2 2 2 0 2 0 2 1 0 2 0 2
 0 1 0 2 0 2 1 2]

Accuracy: 0.69

Comfusion Matrix:
 [[13  0  0]
 [ 0 11  0]
 [ 0 14  7]]


Stuck at work?
Can't find the recipe you are looking for. Let us know and we will find an expert to create the recipe for you. Click here
Companies using this Recipe
2 developers from Infosys
1 developer from EXL Service
1 developer from LTI
1 developer from YASH Technologies
1 developer from Altimetrik
1 developer from HvH
1 developer from MSI Services
1 developer from ANAC
1 developer from MudraCircle
1 developer from Embicon