Question: R studio, machine learning project, which will require the prediction of influence scores of scientific journals ( regression problem ) . dataclean: innerJoin _ ABC

R studio, machine learning project, which will require the prediction of influence scores of scientific journals (regression problem). dataclean: "innerJoin_ABC" . Please use RMSE as evaluation metric. T [1]26987
[1]26986
[1]26946
Rows: 2,694
Columns: 6
$ citation_count_sum 151,2208,3005,537,40,255,30,9,28,71,512,912,70,128,143,109,619,657,230,1432,31...
$ paper_count_sum 106,801,2923,490,67,331,25,15,37,97,447,500,98,131,109,119,537,602,287,483,70,...
$ avg_cites_per_paper 1.4245283,2.7565543,1.0280534,1.0959184,0.5970149,0.7703927,1.2000000,0.6000000,0.7567568,...
$ proj_ai 0.290,0.665,0.192,0.208,0.097,0.134,0.234,0.098,0.131,0.125,0.220,0.396,0.122,0.180,...
$ price 3000,3000,1000,3000,3000,3000,3000,0,0,0,3000,0,0,0,3000,0,0,0,0,3000,3000,30...
$ is_hybrid 1,0,0,1,1,1,1,0,0,0,1,0,0,0,1,0,0,0,0,1,1,1,0,1,0,0,1,1,1,0,0,0,0,...
Rows: 2,694
Columns: 6
$ citation_count_sum 151,2208,3005,537,40,255,30,9,28,71,512,912,70,128,143,109,619,657,230,1432,31...
$ paper_count_sum 106,801,2923,490,67,331,25,15,37,97,447,500,98,131,109,119,537,602,287,483,70,...
$ avg_cites_per_paper 1.4245283,2.7565543,1.0280534,1.0959184,0.5970149,0.7703927,1.2000000,0.6000000,0.7567568,...
$ proj_ai 0.290,0.665,0.192,0.208,0.097,0.134,0.234,0.098,0.131,0.125,0.220,0.396,0.122,0.180,...
$ price 3000,3000,1000,3000,3000,3000,3000,0,0,0,3000,0,0,0,3000,0,0,0,0,3000,3000,30...
$ is_hybrid 1,0,0,1,1,1,1,0,0,0,1,0,0,0,1,0,0,0,0,1,1,1,0,1,0,0,1,1,1,0,0,0,0,...- Data transformation: 1 method for numeric variables and/or 1 method for categorical variables.
-3machine learning algorithms (different types, no models). diferent linear regression and random forest
- Analysis and results
-getting the best prediction model possible.
This may include:
- Additional feature engineering techniques
- Cross-validation
- Additional machine learning algorithms
- Hyper-parameter tuning
-analysis and conclusions.
-create R Markdown file containing the code and the corresponding analysis and conclusions.
- name file as: xx_final.Rmd

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