Exercise

# Build and assess a model: product reviews data

In this exercise, you will build a logistic regression using the `reviews`

dataset, containing customers' reviews of Amazon products. The array `y`

contains the sentiment : `1`

if positive and `0`

otherwise. The array `X`

contains all numeric features created using a BOW approach. Feel free to explore them in the IPython Shell.

Your task is to build a logistic regression model and calculate the accuracy and confusion matrix using the test data set.

The logistic regression and train/test splitting functions have been imported for you.

Instructions

**100 XP**

- Import the accuracy score and confusion matrix functions.
- Split the data into training and testing, using 30% of it as a test set and set the random seed to
`42`

. - Train a logistic regression model.
- Print out the accuracy score and confusion matrix using the test data.