
# coding: utf-8

# In[7]:

# importing data & spliting it:
import numpy as np
def split_X_y (dataset):
    X = dataset.drop ("Target", axis=1) 
    y = dataset["Target"]
    return X, y

def test_case ( test_set, num_instances =100): 
    case_index= np.random.randint(0,len(test_set),num_instances)
    case =test_set.iloc[case_index]
    return case


298032fd6097a0b4efd149e77c2c7fe72e1d1690
<mask token>

<mask token>


def test_case(test_set, num_instances=100):
    case_index = np.random.randint(0, len(test_set), num_instances)
    case = test_set.iloc[case_index]
    return case

<mask token>


def split_X_y(dataset):
    X = dataset.drop('Target', axis=1)
    y = dataset['Target']
    return X, y


def test_case(test_set, num_instances=100):
    case_index = np.random.randint(0, len(test_set), num_instances)
    case = test_set.iloc[case_index]
    return case

import numpy as np


def split_X_y(dataset):
    X = dataset.drop('Target', axis=1)
    y = dataset['Target']
    return X, y


def test_case(test_set, num_instances=100):
    case_index = np.random.randint(0, len(test_set), num_instances)
    case = test_set.iloc[case_index]
    return case


# coding: utf-8

# In[7]:

# importing data & spliting it:
import numpy as np
def split_X_y (dataset):
    X = dataset.drop ("Target", axis=1) 
    y = dataset["Target"]
    return X, y

def test_case ( test_set, num_instances =100): 
    case_index= np.random.randint(0,len(test_set),num_instances)
    case =test_set.iloc[case_index]
    return case

