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Gradient Descent for N features using two datasets: Boston House data, Power Plant Data

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boston-housing-price-prediction feature-scaling gradient-descent gradient-descent-algorithm linear-regression linear-regression-models machine-learning numpy pandas power-plant-predictions sklearn

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gradient Descent CCPP

sir, please tell why we add-ones column in the dataset .please tell me a reason

this is your code
------# ## Add row of ones to testing data
train_ones = np.ones(X_train.shape[0]).reshape(-1, 1)
X_train = np.append(X_train, train_ones, axis=1)

Add row of ones to training data

test_ones = np.ones(X_test.shape[0]).reshape(-1, 1)
X_test = np.append(X_test, test_ones, axis=1)

and another question is that how we recognize which feature affects the cost and how?

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