CODEWITHSUNDEEP
pythonscikit-learn
cookiesRbad
cookiesRbad

Reputation: 45

What is raising the error "Expected 2D array, got 1D array instead..."?

I am working on a ML project and I keep getting this error code when I run my Stochastic Gradient Descent code. Does anyone know why this code occurs or how to fix it? I can provide more information if needed.

My train/test split code:

from sklearn.model_selection import train_test_split

data = mpsc["Sample location (Urban, Rural, Remote)"]

target = mpsc["Total Filament"]

X = data

y = target

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)

X_train

Output for X_train:

523 2

492 3

767 3

440 2

318 1

..

838 2

965 1

518 2

75 3

564 1 Name: Sample location (Urban, Rural, Remote), Length: 806, dtype: object

Output for y_train:

523 0

492 2

767 0

440 0

318 0

..

838 0

965 1

518 0

75 3

564 1 Name: Total Filament, Length: 806, dtype: int64

My SGD code:


    from sklearn.linear_model import SGDRegressor

    sgd_reg = SGDRegressor(max_iter=1000, tol=1e-3, penalty=None, eta0=0.1)

    sgd_reg.fit(X, y.ravel())

My error code:

ValueError: Expected 2D array, got 1D array instead: array=[1. 2. 1. ... 2. 2. 3.]. Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.

Upvotes: 0

Views: 429

Answers (1)

Feline
Feline

Reputation: 784

As the error message suggest, you should reshape your X with X = X.reshape(-1, 1).

You’re getting this error because your X is a 1D array, which you can think of as a Python list. Think of it as [row_1_x, row_2_x, ...]. But sklearn expects a 2D array, a one dimensional vector of multiple features for each row in your data, [[row_1_x], [row_2_x], ...]

Upvotes: 3

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