Databricks Databricks-Certified-Professional-Data-Scientist 問題集

質問 1：
In which of the following scenario you should apply the Bay's Theorem
A. The sample space is partitioned into a set of mutually exclusive events {A1, A2, . .., An }.
B. Within the sample space, there exists an event B, for which P(B) > 0.
C. In all above cases
D. The analytical goal is to compute a conditional probability of the form: P(Ak | B ).
正解：C

質問 2：
Which of the following technique can be used to the design of recommender systems?
A. Collaborative filtering
B. Power iteration
C. 2 and 3
D. 1 and 3
E. Naive Bayes classifier
正解：A
解説: (Topexam メンバーにのみ表示されます)

質問 3：
Which is an example of supervised learning?
A. EM
B. SVD
C. k-means clustering
D. PCA
E. SVM
正解：E
解説: (Topexam メンバーにのみ表示されます)

質問 4：
Which of the following metrics are useful in measuring the accuracy and quality of a recommender system?
A. Support Vector Count
B. Mean Absolute Error
C. Sum of Absolute Errors
D. Cluster Density
正解：B
解説: (Topexam メンバーにのみ表示されます)

質問 5：
You are using k-means clustering to classify heart patients for a hospital. You have chosen Patient Sex, Height, Weight, Age and Income as measures and have used 3 clusters. When you create a pair-wise plot of the clusters, you notice that there is significant overlap between the clusters. What should you do?
A. Increase the number of clusters
B. Remove one of the measures
C. Decrease the number of clusters
D. Identify additional measures to add to the analysis
正解：C

質問 6：
You are designing a recommendation engine for a website where the ability to generate more personalized recommendations by analyzing information from the past activity of a specific user, or the history of other users deemed to be of similar taste to a given user. These resources are used as user profiling and helps the site recommend content on a user-by-user basis. The more a given user makes use of the system, the better the recommendations become, as the system gains data to improve its model of that user. What kind of this recommendation engine is ?
A. Collaborative filtering
B. Content-based filtering
C. Logistic Regression
D. Naive Bayes classifier
正解：A
解説: (Topexam メンバーにのみ表示されます)

質問 7：
A data scientist is asked to implement an article recommendation feature for an on-line magazine.
The magazine does not want to use client tracking technologies such as cookies or reading history. Therefore, only the style and subject matter of the current article is available for making recommendations. All of the magazine's articles are stored in a database in a format suitable for analytics.
Which method should the data scientist try first?
A. K Means Clustering
B. Logistic Regression
C. Naive Bayesian
D. Association Rules
正解：A
解説: (Topexam メンバーにのみ表示されます)

質問 8：
What are the advantages of the mutual information over the Pearson correlation for text classification problems?
A. The mutual information doesn't assume that the variables are normally distributed.
B. The mutual information has a meaningful test for statistical significance.
C. The mutual information can signal non-linear relationships between the dependent and independent variables.
D. The mutual information is easier to parallelize.
正解：D
解説: (Topexam メンバーにのみ表示されます)