Answer:
b
Explanation:
First, we need to initialize the classifier.
Then, we are required to train the classifier.
The next step is to predict the target.
And finally, we need to evaluate the classifier model.
You will find different algorithms for solving the classification problem. Some of them are like decision tree classification etc.
However, you need to know how these classifier works. And its explained before:
You need to initialize the classifier at first.
All kinds of classifiers in the scikit-learn make use of the method fit(x,y) for fitting the model or the training for the given training set in level y.
The predict(x) returns the y which is the predicted label.And this is prediction.
For evaluating the classifier model- the score(x,y) gives back the certain score for a mentioned test data x as well as the test label y.
I think the best one is voice recognition keyboards.
Would perfect work there
Mark as brainliest
Answer:
C) Hardware, Software, People
Explanation:
System design is the determination of the overall system architecture-consisting of a set of physical processing components, Hardware, Software, People and the communication among them-that will satisfy the system’s essential requirements.
Solution :
class Employee:
#Define the
#constructor.
def __
__(
, ID_number, 
, email):
#Set the values of
#the data members of the class.
= name
_number = ID_number
= salary
self.email_address = email
#Define the function
#make_employee_dict().
def make_employee_dict(list_names, list_ID, list_salary, list_email):
#Define the dictionary
#to store the results.
employee_dict = {}
#Store the length
#of the list.
list_len = len(list_ID)
#Run the loop to
#traverse the list.
for i in range(list_len):
#Access the lists to
#get the required details.
name = list_names[i]
id_num = list_ID[i]
salary = list_salary[i]
email = list_email[i]
#Define the employee
#object and store
#it in the dictionary.
employee_dict[id_num] = Employee(name, id_num, salary, email)
#Return the
#resultant dictionary.
return employee_dict
