MeTTa + Clustering

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Expert Rating 1.6
firefly_ross
Project Owner

MeTTa + Clustering

Expert Rating

1.6

Overview

no chatgpt. kmeans and other clustering algos will be implemented with all required metrics.

RFP Guidelines

Implement clustering heuristics in MeTTa

Complete & Awarded
  • Type SingularityNET RFP
  • Total RFP Funding $40,000 USD
  • Proposals 6
  • Awarded Projects 1
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SingularityNET
Aug. 12, 2024

The goal is to implement clustering algorithms in MeTTa and demonstrate interesting functionality on simple but meaningful test problems. This serves as a working prototype providing guidance for development of scalable tooling providing similar functionality, suitable for serving as part of a Hyperon-based AGI system following the PRIMUS cognitive architecture.

Proposal Description

Open Source Licensing

GNU GPL - GNU General Public License

open source push to github

Proposal Video

Not Avaliable Yet

Check back later during the Feedback & Selection period for the RFP that is proposal is applied to.

  • Total Milestones

    3

  • Total Budget

    $15,000 USD

  • Last Updated

    22 Nov 2024

Milestone 1 - Clustering methods

Description

metta implementation of all 4 clustering methods

Deliverables

K-Means Hierarchical Clustering Spectral Clustering Gaussian Mixture Model (GMM)

Budget

$8,000 USD

Milestone 2 - Eval metrics

Description

module to eval clustering algorithms

Deliverables

Rand Index Mutual Information Purity/Homogeneity Measure

Budget

$6,000 USD

Milestone 3 - Output visualization

Description

output visualization

Deliverables

output visualization module

Budget

$1,000 USD

Join the Discussion (0)

Expert Ratings

Reviews & Ratings

Group Expert Rating (Final)

Overall

1.6

  • Compliance with RFP requirements 2.3
  • Solution details and team expertise 2.0
  • Value for money 1.3
  • Expert Review 1

    Overall

    1.0

    • Compliance with RFP requirements 1.0
    • Solution details and team expertise 1.0
    • Value for money 0.0
    incomplete

    I have the following three comments about all the clustering proposals and to be fair, I will mention them for all the proposals. At the end, you can see my comments specifically for this current proposal. First, I was expecting to see more on the difficulties that one may face when a clustering algorithm is implemented in MeTTa, in other words, MaTTa-specific challenges, and the proposing team plans to handle them. I did not see that in any of the proposals. Second, I was expecting to see their plan for making sure the MeTTa clustering library will have the ability to work robustly on diverse datasets. For example, they could have listed a few datasets that may cause problems for a clustering algorithm and could have mentioned how they plan to avoid those problems. Third, based on my experience with clustering algorithms, most computational gains come from vectorization. None of the proposals even mention that even though the RFP specifically mentions Concurrent processing and the ability to work on large datasets. Proposal-specific comments: This proposal is not complete.

  • Expert Review 2

    Overall

    2.0

    • Compliance with RFP requirements 4.0
    • Solution details and team expertise 1.0
    • Value for money 0.0
    it's much to sketchy, not a full proposal

  • Expert Review 3

    Overall

    2.0

    • Compliance with RFP requirements 2.0
    • Solution details and team expertise 2.0
    • Value for money 0.0

    Most basic of information is provided. Hard to distinguish but that is also the nature of this particular RFP.

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