Complete the following prototype function (it is fine if you reuse your code from the last problem set.- but make sure that it actually works as expectedi) In : def prototype(features): Compute the prototype features, based on the given features of category members. The prototype should have a feature if half or more of the category members have that feature. Hint: you can use your implementation of 'prototype from the last problem set here, though you may want to cast the array to integers to match the format elsewhere (try.astype(int).). Your solution can be done in 1 line of code (including the return statement) Parameters features numpy array with shape (n, m) The first dimension corresponds to n category members, and the second dimension to m features. Returns numpy array with shape (m,) corresponding to the features of the prototype of the category members # YOUR CODE HERE Complete the following prototype function (it is fine if you reuse your code from the last problem set.- but make sure that it actually works as expectedi) In : def prototype(features): Compute the prototype features, based on the given features of category members. The prototype should have a feature if half or more of the category members have that feature. Hint: you can use your implementation of 'prototype from the last problem set here, though you may want to cast the array to integers to match the format elsewhere (try.astype(int).). Your solution can be done in 1 line of code (including the return statement) Parameters features numpy array with shape (n, m) The first dimension corresponds to n category members, and the second dimension to m features. Returns numpy array with shape (m,) corresponding to the features of the prototype of the category members # YOUR CODE HERE