Answer:
(B) A sales professional writes a presentation for customers to navigate to products of interest.
(D) An instructor selects slides to answer questions from students about the lecture.
Explanation:
answers are for e2020
Answer:
The various reasons that could be a major problem for the implementation are it involves a large number of parameters also, having a noisy data
Explanation:
Solution
The various reasons that could be causing the problem is given as follows :
1. A wide number of parameters :
-
In the ensemble tree method, the number of parameters which are needed to be trained is very large in numbers.
- When the training is performed in this tree, then the model files the data too well.
- When the model has tested against the new data point form the validation set, then this causes a large error because the model is trained completely according to the training data.
2. Noisy Data:
- The data used to train the model is taken from the real world . The real world's data set is often noisy i.e. contains the missing filed or the wrong values.
- When the tree is trained on this noisy data, then it sets its parameters according to the training data.
- As regards to testing the model by applying the validate set, the model gives a large error of high in accuracy
y.
n = int(input("How many numbers do you need to check? "))
even = 0
odd = 0
for x in range(n):
num = int(input("Enter number: "))
if num % 2 == 0:
even += 1
print(str(num) + " is an even number.")
else:
odd += 1
print(str(num) + " is an odd number.")
print("You entered " + str(even) + " even number(s).")
print("You entered " + str(odd) + " odd number(s).")
This works for me. Best of luck.
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