Tasks:
1. mine association rules using apriori ( min support - 0.05 , confidence - 20%)
2. Generalize each GO annotation in your input file by replacing with its parent as noted in the attached file ([login to view URL]). Mine rules after each [login to view URL]
3. the GO terms are hierarchial – mine relations.
[login to view URL] tsv file – – replace it with direct parents – if repeats pick randomly – u have new set now – mine assoc rules .
5. 2nd round of replacement – opposite of 1st round of replacement – replace the already replaced parents with 2nd direct parents. Now you have 3 transaction sets. From each of 3 sets, mine assoc rules and put these rules together.
6. If u get rules x implies y, x implies (y ,z), just put x implies y.
4. If x implies y, if x is parent or y is parent, remove the rule- find these in text file.
5. If x is child of z, y implies z , infer the relation from go file.- get all the ancestors – say y and z are ancestors of x .
6. Filter any rules between an ancestor and child. Get ancestor children relationships from the [login to view URL] file. – remove x im y , y imp z , remove these both rules. Remaining – go terms that r not related .
Hi, I'm able to do this task and interested. please contact me to discuss more about it. I have done Master's in this domain and working as a data scientist.
We are new on freelancer but we have well-experienced team who have more than 4 years of experience.
Give us an opportunity so that we can work with you.
Let me know a good time when we can discuss it in detail and when we can start.
Thanks & Regards
V2infotech
hello sir, I reviewed your project througly and I am glad to do your project as I can complete your project as required by you,so plz sir offer me this job. thank you