Mid Term

   Please acknowledgment the afterward questions: 1. As the Big Abstracts ecosystem takes shape, there are four capital groups of players aural this commutual web. List and explain those groups. 2. How the abstracts science aggregation appraise whether the archetypal is abundantly able-bodied to break the botheration or not? What are the questions that they should ask? 3. Explain the differences amid Hexbinplot and Scatterplot and back to use anniversary one of them. 4. k-means does not handle absolute data? 5. bounded banker has a database that food 10,000 affairs of aftermost summer. After allegory the data, a abstracts science aggregation has articular the afterward statistics: ● {battery} appears in 6,000 transactions. ● {sunscreen} appears in 5,000 transactions. ● {sandals} appears in 4,000 transactions. ● {bowls} appears in 2,000 transactions. ● {battery, sunscreen} appears in 1,500 transactions. ● {battery, sandals} appears in 1,000 transactions. ● {battery, bowls} appears in 250 transactions. ● {battery, sunscreen, sandals} appears in 600 transactions. Answer the afterward questions: a. What are the abutment ethics of the above-mentioned itemsets? b. Assuming the minimum abutment is 0.05, which itemsets are advised frequent? 6. Linear corruption is an analytic address acclimated to archetypal the accord amid several ascribe variables and a connected aftereffect variable. Linear corruption can be acclimated in business, government, and medical. Explain by archetype how it can be acclimated in those domains. 7. Which classifier is advised computationally able for high-dimensional problems? Why? 8. Define the afterward time alternation components: ● Trend ● Seasonality ● Cyclic ● Random

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