# ds1000 / 911

- taskset: [ds1000](https://harnessreport.com/tasks/ds1000.md)
- difficulty: 
- category: 
- language: 
- runnable from the site: no
- agent timeout: 1800s

## Results by harness

_none yet_

## Instruction

```
# 911: DS-1000 Task

## Prompt
Problem:

I am trying to run an Elastic Net regression but get the following error: NameError: name 'sklearn' is not defined... any help is greatly appreciated!

    # ElasticNet Regression

    from sklearn import linear_model
    import statsmodels.api as sm

    ElasticNet = sklearn.linear_model.ElasticNet() # create a lasso instance
    ElasticNet.fit(X_train, y_train) # fit data

    # print(lasso.coef_)
    # print (lasso.intercept_) # print out the coefficients

    print ("R^2 for training set:"),
    print (ElasticNet.score(X_train, y_train))

    print ('-'*50)

    print ("R^2 for test set:"),
    print (ElasticNet.score(X_test, y_test))

A:

corrected code
<code>
import numpy as np
import pandas as pd
from sklearn import linear_model
import statsmodels.api as sm
X_train, y_train, X_test, y_test = load_data()
assert type(X_train) == np.ndarray
assert type(y_train) == np.ndarray
assert type(X_test) == np.ndarray
assert type(y_test) == np.ndarray
</code>
training_set_score, test_set_score = ... # put solution in these variables
BEGIN SOLUTION
<code>

## What to do
- Edit `solution/solution.py` so the code passes the DS-1000 tests.
- Do not access the internet or install new packages; required libraries are preinstalled in the Docker image.
- Run tests locally via `bash tests/test.sh`.

## Notes
- Keep the variable names/signatures implied by the prompt/code_context.
- The evaluator uses the original DS-1000 `code_context` (`test_execution` / `test_string`).
```
---
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