[Solved] What is wrong with this pipeline code snippet?from sklearn.pipeline import Pipeline from sklearn.preprocessing import FunctionTransformer import numpy as np def add_one(x):... | SciPy

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What is wrong with this pipeline code snippet?

from sklearn.pipeline import Pipeline
from sklearn.preprocessing import FunctionTransformer
import numpy as np

def add_one(x):
    return x + 1

pipe = Pipeline([
    ('add', FunctionTransformer(add_one, validate=False))
])

X = [1, 2, 3]
pipe.transform(X)

APipeline cannot have only one step

BFunctionTransformer requires validate=true for lists

CInput X should be a numpy array, not a list

Dadd_one function must be vectorized

Step-by-Step Solution

Solution:

Step 1: Check input type
FunctionTransformer expects numpy arrays by default; list input may cause errors.
Step 2: Validate input
Passing list without conversion can cause unexpected behavior or errors.
Final Answer:
Input X should be a numpy array, not a list -> Option C
Quick Check:
Use numpy arrays for transformations [OK]

Quick Trick: Always use numpy arrays with scikit-learn transformers [OK]

Common Mistakes:

Passing lists directly to transformers
Misunderstanding validate parameter
Thinking single-step pipelines are invalid

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What is wrong with this pipeline code snippet?

Step 1: Check input type

Step 2: Validate input

Final Answer:

Quick Check:

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