A. A very large database, or VLDB, is a database that contains an extremely large number of tuples (database rows), or occupies an extremely large physical file system storage space. A one terabyte database would normally be considered to be a VLDB.
Q. Tell me some of Classification Algorithms?
A. Linear Classifiers: Logistic Regression, Naive Bayes Classifier, Decision Trees, Random Forest, Neural Networks, K Nearest Neighbor.
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Q. What are pros and cons of Naive Bayes algorithm ?
A. Big sized data is handled easily
Multiclass performance is good and accurate
It is not process intensive
Cons: Assume an independence of predictor variables.
Q. Explain the types of Skewness Data Science?
A. A dataset that is skewed right or left are the two types.
Q. What is skewed data?
A. A data distribution that is has skewed data towards the right or left.
Q. What is the skewness of this data presented in data science?
A. Ex- 26 ; 28 ; 31 ; 32 ; 34 ; 39 ; 41 ; 43 ; 44 ; 45 ; 46 ; 53 ; 58 ; 64
The data set is skewed left.
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