Nikan Doosti K-MCI Issues

Nikronic/K-MCI Issues

Influence each center fitness to algorithm instead of candidate fitness
Updated 5 years ago1
Paper's numbers
Closed 5 years ago2
Fitness function implementation not matched with paper
Updated 5 years ago
Answer
Closed 6 years ago1
Build Kmeans class with new Fitness function instead the internal one
Closed 6 years ago1
Our standardization method should give higher fitness compare to article fitness.
Closed 6 years ago1
Sampling Intervals
Closed 6 years ago1
Number of iteration in Kmean algorithm not defined.
Closed 6 years ago
Selecting random between mutated candidate and original candidate.
Closed 6 years ago1
Mutation problem
Updated 6 years ago
Selecting random between mutated candidate and original candidate.
Closed 6 years ago
K-means++ for initial centers is **WRONG**
Closed 6 years ago3
Getting all necessary variables for Candidate parametrs as Kmean fit
Closed 6 years ago2
convergence parameter not specified in the article.
Updated 6 years ago2
Jupyter notebook cannot understand any changes in our classes. So we have to copy all code to the jupyter and remove our classes. So sorry for this big problem in Jupyter and Python.
Closed 6 years ago
Assignment
Closed 6 years ago2
Why you assigning sampling_intervals to clusters_centers for fitting Kmean?
Closed 6 years ago1
We need initial of centers in K-Means algorithm
Closed 6 years ago1
'TypeError: 'Candidate' object does not support item assignment
Closed 6 years ago1
I think we should start main algorithm of project on Jupyter Notebook
Closed 6 years ago1
initial candidates - Hamed
Closed 6 years ago2

Nikronic / K-MCI

Nikronic/K-MCI Issues

Influence each center fitness to algorithm instead of candidate fitness

Paper's numbers

Fitness function implementation not matched with paper

Answer

Build Kmeans class with new Fitness function instead the internal one

Our standardization method should give higher fitness compare to article fitness.

Sampling Intervals

Number of iteration in Kmean algorithm not defined.

Selecting random between mutated candidate and original candidate.

Mutation problem

Selecting random between mutated candidate and original candidate.

K-means++ for initial centers is WRONG

Getting all necessary variables for Candidate parametrs as Kmean fit

convergence parameter not specified in the article.

Jupyter notebook cannot understand any changes in our classes. So we have to copy all code to the jupyter and remove our classes. So sorry for this big problem in Jupyter and Python.

Assignment

Why you assigning sampling_intervals to clusters_centers for fitting Kmean?

We need initial of centers in K-Means algorithm

'TypeError: 'Candidate' object does not support item assignment

I think we should start main algorithm of project on Jupyter Notebook

initial candidates - Hamed