Get rid of the disrupting points

$30-250 CAD

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ponad 5 lat temu

$30-250 CAD

Płatne przy odbiorze

On the uploaded pictures, we can identify two clouds (i.e. red and blue clouds). We can identify a lot of points that are out of the two clouds and can disrupt a bit the the training and test accuracy (%). Is there an unsupervised machine learning model or other techniques we can use to get rid of those points? I thought to try to train a neural network to maximize inter class distances, but minimize intra class distances, but it is a bit unclear.

Data Analytics

Machine Learning (ML)

Mathematics

Python

Identyfikator projektu: 17373568

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Aktywny 6 lat temu

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8 freelancerzy składają oferty o średniej wysokości $183 CAD dla tej pracy

@schoudhary1553

Hello, I can help with you in your project to train a neural network to maximize inter class distances. Relevant Skills and Experience I have more than 5 years of experience in Data Analytics, Machine Learning, Mathematics, Python. We have worked on several similar projects before! Proposed Milestones $250 CAD - unsupervised machine learning

$250 CAD w 3 dni

4,9

(49 opinii)

6,1

@mlagunas

I think this problem could be solved using traditional statistics. However, if the traditional statistical methods do not work machine learning approaches might be beneficial. Let's discuss this! Relevant Skills and Experience Currently, I am a PhD candidate working on the interface between machine learning and computer graphics. Before I did a bachelor in computer science and a master's degree in applied maths. Proposed Milestones $35 CAD - Discuss the approach to follow $55 CAD - Implementation of this approach $87 CAD - Validation of the code/approach Currently, I am a PhD candidate working on the interface between machine learning and computer graphics. Before I did a bachelor in computer science and a master's degree in applied maths. My everyday job consists on implementing/testing machine learning algorithms applied to computer graphics problems. In particular, now I work on how to obtain light reflectance in a media using convolutional neural networks and on obtaining the perceptual parameters that people use to identify materials to use it as a prior in the design of robust and explainable algorithms.

$177 CAD w 3 dni