吴恩达机器学习第一周测试

测试1

第1题

答案
A

第2题

答案
Classification
分析：预测是否下雨，则可以看出预测值已经确定了：要么下雨，要么不下，是个分类问题。

第3题

答案
Classification
分析：同上题，这题预测是否破产，很明显预测结果已经是要么破产，要么不破产，分类问题。

第4题

答案
BC
分析：
A:给出一组数据，将同一类型的人归类，典型的聚类算法，属于无监督学习。
B：分出人声和乐器声，分类算法，监督学习。
C：通过DNA数据分析是否会患糖尿病，是分类算法，属于监督学习。
D：将病人划分至不同的类别，是聚类算法，属于无监督学习。

第5题

答案
C

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测试2

第1题

Consider the problem of predicting how well a student does in her second year of college/university, given how well she did in her first year.

Specifically, let x be equal to the number of “A” grades (including A-. A and A+ grades) that a student receives in their first year of college (freshmen year). We would like to predict the value of y, which we define as the number of “A” grades they get in their second year (sophomore year).

Refer to the following training set of a small sample of different students’ performances (note that this training set may also be referenced in other questions in this quiz). Here each row is one training example. Recall that in linear regression, our hypothesis is , and we use mm to denote the number of training examples.

For the training set given above, what is the value of mm? In the box below, please enter your answer (which should be a number between 0 and 10).

答案
4
分析：很简单

第2题

Consider the following training set of m=4m=4 training examples:

x	y
1	0.5
2	1
4	2
0	0

Consider the linear regression model
What are the values of θ0 and θ1 that you would expect to obtain upon running gradient descent on this model? (Linear regression will be able to fit this data perfectly.)

答案
theta0 = 0, theta1 = 0.5
分析：带入选项，选择最适合的

第3题

Suppose we set theta0 = 0, theta1 = 1.5 in the linear regression hypothesis from Q1. What is h_theta_x(3)?

答案
3
​分析：带入即可算出

第4题

答案

分析：Plot1为等高线图，A点应为最小值点，与之对应为Plot2中的P点。

第5题

答案
A
分析：
对于A：毫无疑问时对的，损失函数为0说明，预测值与实际值一模一样，故为一条直线。
对于B：我之前选了，但是这个选项不对。因为从Plot2中可以看出，在这个例子中局部极小值就是全局最小值，故不会卡在局部出不来。（但是脱离这个例子，这句话就是对的，毕竟找到全局最小值是一个概率事件）
对于C和D：损失函数为0 与 theta与y并无直接关系。

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测试3

第1题

答案
D

第2题

答案
D

第3题

答案
C

第4题

答案
13

第5题

答案
A C