SQL Joins

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Joins are used to combine rows from two or more tables based on related columns between them. Joins allow you to retrieve data from multiple tables simultaneously, enabling you to create complex queries that fetch data from different sources. There are different types of joins in SQL, including: INNER JOIN Returns only the rows that have matching values in both tables based on the specified join condition. It discards non-matching rows from both tables. Example:           create table t1(x int); insert into t1 values(1); insert into t1 values(1); insert into t1 values(0); create table t2(y int); insert into t2 values(0); insert into t2 values(1); insert into t2 values(1);           select * from t1 inner join t2 on t1.x = t2.y Output: 2. LEFT JOIN (or) LEFT OUTER JOIN Returns all the rows from the left (or first) table and the matching rows from the right (or second) table. If there is no match, NULL values are
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Machine Learning Foundation Clustering and Similarity Quiz Answers

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1) A country, called Simpleland, has a language with a small vocabulary of just “the”, “on”, “and”, “go”, “round”, “bus”, and “wheels”. For a word count vector with indices ordered as the words appear above, what is the word count vector for a document that simply says “the wheels on the bus go round and round.”

Please enter the vector of counts as follows: If the counts were ["the"=1, “on”=3, "and"=2, "go"=1, "round"=2, "bus"=1, "wheels"=1], enter 1321211.

Enter answer here

2111211

2) In Simpleland, a reader is enjoying a document with a representation: [1 3 2 1 2 1 1]. Which of the following articles would you recommend to this reader next?

a) [7 0 2 1 0 0 1]
b) [1 7 0 0 2 0 1]
c) [1 0 0 0 7 1 2]
d) [0 2 0 0 7 1 1]

3) A corpus in Simpleland has 99 articles. If you pick one article and perform 1-nearest neighbor search to find the closest article to this query article, how many times must you compute the similarity between two articles?

a) 98
b) 98*2 = 196
c) 98/2 = 49
d) (98)^2
e) 99

4) For the TF-IDF representation, does the relative importance of words in a document depend on the base of the logarithm used? For example, take the words "bus" and "wheels" in a particular document. Is the ratio between the TF-IDF values for "bus" and "wheels" different when computed using log base 2 versus log base 10?

a) Yes
b) No

5) Which of the following statements are true? (Check all that apply):

a) Deciding whether an email is spam or not spam using the text of the email and some spam / not spam labels is a supervised learning problem.
b) Dividing emails into two groups based on the text of each email is a supervised learning problem.
c) If we are performing clustering, we typically assume we either do not have or do not use class labels in training the model.

6) Which of the following pictures represents the best k-means solution? (Squares represent observations, plus signs are cluster centers, and colors indicate assignments of observations to cluster centers.)

b

Comments

  1. UnknownJune 3, 2020 at 7:12 AM

    what is the answer for q5?

    ReplyDelete
    Replies
    1. UnknownJune 3, 2020 at 7:15 AM

      ans for q5 is 1,3

      Delete
    2. AnonymousApril 20, 2022 at 12:42 AM

      Machine Learning Foundation Clustering And Similarity Quiz Answers >>>>> Download Now

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  2. UnknownJune 20, 2020 at 5:39 AM

    can anyone give explaination of q1-3??......

    ReplyDelete
  3. UnknownJuly 18, 2020 at 2:03 AM

    answer for question 4 is YES

    ReplyDelete

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