MOOC 交通数据挖掘技术(Data Mining for Transportation)-东南大学 中国大学慕课答案.docx
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1、 MOOC 交通数据挖掘技术(Data Mining forTransportation)-东南大学 中国大学慕课答案Test 11、问题:Which one is not the description of Data mining?选项:A、Extraction of interesting patterns or knowledgeB、Explorations and analysis by automatic or semi-automatic meansC、Discover meaningful patterns from large quantities of dataD、Appr
2、opriate statistical analysis methods to analyze the data collected正确答案:【Appropriate statistical analysis methods to analyze the data collected】2、问题:Which one describes the right process of knowledge discovery?选项:A、Selection-Preprocessing-Transformation-Data mining-Interpretation/EvaluationB、Preproce
3、ssing-Transformation-Data mining- Selection- Interpretation/EvaluationC、Data mining- Selection- Interpretation/Evaluation- Preprocessing-TransformationD、Transformation-Data mining- election-Preprocessing- Interpretation/Evaluation正确答案:【Selection-Preprocessing-Transformation-Data mining-Interpretatio
4、n/Evaluation】3、问题:Which one is not belong to the process of KDD?选项:A、Data miningB、Data descriptionC、Data cleaningD、Data selection正确答案:【Data description】4、问题:Which one is not the right alternative name of data mining?选项:A、Knowledge extractionB、Data archeologyC、Data dredgingD、Data harvesting正确答案:【Data
5、 harvesting】5、问题:Which one is not the nominal variables?选项:A、Occupation B、EducationC、AgeD、Color正确答案:【Age】6、问题:Which one is wrong about classification and regression?选项:A、Regression analysis is a statistical methodology that is most often used for numericprediction.B、We can construct classification m
6、odels (functions) without some training examples.C、Classification predicts categorical (discrete, unordered) labels.D、Regression models predict continuous-valued functions.正确答案:【We can construct classification models (functions) without some trainingexamples.】7、问题:Which one is wrong about clustering
7、 and outliers?选项:A、Clustering belongs to supervised learning.B、Principles of clustering include maximizing intra-class similarity and minimizinginterclass similarity.C、Outlier analysis can be useful in fraud detection and rare events analysis.D、Outlier means a data object that does not comply with t
8、he general behavior of thedata.正确答案:【Clustering belongs to supervised learning.】8、问题:About data process, which one is wrong?选项:A、When making data discrimination, we compare the target class with one or a set ofcomparative classes (the contrasting classes).B、When making data classification, we predic
9、t categorical labels excluding unorderedone.C、When making data characterization, we summarize the data of the class under study(the target class) in general terms.D、When making data clustering, we would group data to form new categories.正确答案:【When making data classification, we predict categorical l
10、abels excludingunordered one.】9、问题:Outlier miningsuch as density based method belongs to supervised learning.选项:A、正确B、错误正确答案:【错误】 10、问题:Support vector machines can be used for classification and regression.选项:A、正确B、错误正确答案:【正确】Test 21、问题:Which is not the reason we need to preprocess the data?选项:A、to
11、save timeB、to make result meet our hypothesisC、to avoid unreliable outputD、to eliminate noise正确答案:【to make result meet our hypothesis】2、问题:Which is not the major tasks in data preprocessing?选项:A、CleanB、IntegrationC、TransitionD、Reduction正确答案:【Transition】3、问题:How to construct new feature space by PCA?
12、选项:A、New feature space by PCA is constructed by choosing the most important featuresyou think.B、New feature space by PCA is constructed by normalizing input data.C、New feature space by PCA is constructed by selecting features randomly.D、New feature space by PCA is constructed by eliminating the weak
13、 components toreduce the size of the data.正确答案:【New feature space by PCA is constructed by eliminating the weakcomponents to reduce the size of the data.】4、问题:Which one is wrong about methods for discretization?选项:A、Histogram analysis and Binging are both unsupervised methods.B、Clustering analysis o
14、nly belongs to top-down split.C、Interval merging by c2 Analysis can be applied recursively.D、Decision-tree analysis is Entropy-based discretization.正确答案:【Clustering analysis only belongs to top-down split.】 5、问题:Which one is wrong about Equal-width (distance) partitioning and Equal-depth (frequency)
15、 partitioning?选项:A、Equal-width partitioning is the most straightforward, but outliers may dominatepresentation.B、Equal-depth partitioning divides the range into N intervals, each containingapproximately same number of samples.C、The interval of the former one is not equal.D、The number of tuples is th
16、e same when using the latter one.正确答案:【The interval of the former one is not equal.】6、问题:Which one is wrong way to normalize data?选项:A、Min-max normalizationB、Simple scalingC、Z-score normalizationD、Normalization by decimal scaling正确答案:【Simple scaling】7、问题:Which are the right way to fill in missing va
17、lues?选项:A、Smart meanB、Probable valueC、IgnoreD、Falsify正确答案:【Smart mean#Probable value#Ignore】8、问题:Which are the right way to handle noise data?选项:A、RegressionB、ClusterC、WTD、Manual正确答案:【Regression#Cluster#WT#Manual】9、问题:Which one is right about wavelet transforms?选项:A、Wavelet transforms store large fr
18、actions of the strongest of the wavelet coefficients.B、The DWT decomposes each segment of time series via the successive use of low-pass and high-pass filtering at appropriate levels.C、Wavelet transforms can be used for reducing data and smoothing data.D、Wavelet transforms means applying to pairs of
19、 data, resulting in two set of data ofthe same length. 正确答案:【The DWT decomposes each segment of time series via the successive use oflow-pass and high-pass filtering at appropriate levels.#Wavelet transforms can be usedfor reducing data and smoothing data.】10、问题:Which are the common used ways to sam
20、pling?选项:A、Simple random sample without replacementB、Simple random sample with replacementC、Stratified sampleD、Cluster sample正确答案:【Simple random sample without replacement#Simple random sample withreplacement#Stratified sample#Cluster sample】11、问题:Discretization means dividing the range of a continu
21、ous attribute intointervals.选项:A、正确B、错误正确答案:【正确】Test 31、问题:Whats the difference between eager learner and lazy learner?选项:A、Eager learners would generate a model for classification while lazy learner wouldnot.B、Eager learners classify the turple based on its similarity to the stored training turplew
22、hile lazy learner not.C、Eager learners simply store data (or does only a little minor processing) while lazylearner not.D、Lazy learner would generate a model for classification while eager learner would not.正确答案:【Eager learners would generate a model for classification while lazy learnerwould not.】2
23、、问题:How to choose the optimal value for K?选项:A、Cross-validation can be used to determine a good value by using an independentdataset to validate the K values.B、Low values for K (like k=1 or k=2) can be noisy and subject to the effect of outliers.C、A large k value can reduce the overall noise so the
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