The fourth choice is correct.
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.
Answer:
Here is the Python program which has a function sum_scores:
def sum_scores(score1, score2, score3, score4):
sum = score1 + score2 + score3 + score4
print(sum)
sum_scores(14,7,3,0)
Explanation:
- Method sum_scores takes four arguments, score1, score2, score3, score4.
- The sum variable adds these four scores and stores the value of their addition.
- Lastly print statement is used to print the value stored in sum variable which is the value obtained by adding the four scores.
- Last statement calls the sum_scores method and passes four values to it which are 14,7,3,0
- The output of the above program is:
- 24
- If you want to use return statement instead of print statement you can replace print(sum) with return sum. But in order to display the sum of the scores you can replace sum_scores(14,7,3,0) with print(sum_scores(14,7,3,0))
- The program along with the output is attached as a screenshot.
Answer:
Big Oh notation is used to asymptotically bound the growth of running time above and below the constant factor.
Big Oh notation is used to describe time complexity, execution time of an algorithm.
Big Oh describes the worst case to describe time complexity.
For the equation; T(N) = 10000*N + 0.00001*N^3.
To calculate first of all discard all th constants.
And therefore; worst case is the O(N^3).
Agreed to all the terms mentioned in the contract
