Write Algorithm for Ordered weighted aggregation. OWA(M,W) in: sequence of membership values M; sequence of weights W out: aggregated result

it says relation guest doesnt exist am i making a guess table

Resolving collisions by using buckets that are linked chains is called. list resolution separate chaining bucket chaining O linked chaining

A split at the $3200 income point creates a top and bottom partition. Compute the overall(weighted) Gini index given an income split of 32000. income is 0, 10,000, 20,000, 30,000, 40,000, 50,000, 60,000, 70,000, 80,000, and age is 0,10,20,30,40,50 (Please give correct answer with explanction)

solve 6a,b,c Please include all the steps and reasonings and kindly make sure the answer is correct and properly formatted. Thank you

Please solve the attached recurrence relation.

Please help me with this recurrence relation: B(0) = 1, B(n) = B(n −1) + n + 3  for  n > 0 Use the method of unraveling to find a closed form for B(n).

Explain how to split the hybrid hash-join operator into sub-operators to model pipelining

You could save the names of restaurants together with their x, y locations in a database. Just think about the following questions: The primary concern of the inquiry is to determine whether a dining establishment exists. Optimal approach to indexing: Which is better, a B-tree or an R-tree? Why?

We  use  the  Breast  Cancer  Wisconsin  dataset  from  UCI  machine  learning  repository: http://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+%28Diagnostic%29 Data File: breast-cancer-wisconsin.data (class: 2 for benign, 4 for malignant) Data Metafile: breast-cancer-wisconsin.names  Please  implement  this  algorithm  for  logistic  regression  (i.e.,  to  minimize  the  cross-entropy loss as discussed in class), and run it over the Breast Cancer Wisconsin dataset. Please  randomly  sample  80%  of  the  training  instances  to  train  a  classifier  and  then testing it on the remaining 20%. Ten such random data splits should be performed and the average over these 10 trials is used to estimate the generalization performance. You  are  expected  to  do  the  implementation  all  by  yourself  so  you  will  gain  a  better understanding of the method. Please submit: (1) your source code (or Jupyter notebook file) that TA should be able to (compile  and) run, and the…