Data Mining Using R Software - open to bidding
$30-250 USD
Paid on delivery
Use the data as transformed (see the files mean [login to view URL], median [login to view URL]) .Train the classifiers using
2/3 of the data from step 1(the mentioned files) and test the classifiers by applying them to the remaining 1/3 of the data
from step 1(the mentioned files). In this part you will be predicting the Class2 feature of the data (binary classification
CTY or non-CYT) using the first 8 features (mcg-nuc).
a) Classification
Try using the following classification algorithms: Naive Bayes, k-NN (k=5 and k=10),
logistic regression and C4.5 Decision tree algorithms. What are the algorithms accuracies on
the test data? Explain the results.
b) Ensembles
Create a stacker ensemble: Use the output for each of the previous classifiers as features into
a new classifier of your choice (this may require changing your train/test split). Illustrate what
is being done and give an example of how it works. How does the performance compare with
each single classifier?
c) Conclude :What are the potential issues/limitations with stacking?
Project ID: #7711433
About the project
8 freelancers are bidding on average $176 for this job
Hi sir, I am scraping expert, I have did too many similar projects, please check my feedback then you will know. Can you tell me more details? then I will provide demo data for you. Thanks, Kimi
Thanks for posting an interesting project and give an opportunity to place my bid. Could you Pattach excel files with data that you mentioned in the project description? Thanks
Hi.. Expert Web Scraper & Data Minor here. I have done too many similar project in past. Having best scraping tools and experience i assure you 100% accurate and good quality work.