Fix my Django Application using PCA/Sklearn Model to predict new input

$30-250 AUD

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All application is working. The logic of the application is, to classify the user input, which they provide, and classify them as 0 or 1. I am using PCA (n_components = 25) which take train data and convert it to pca(n=25), this is model input, but what it does in real time, it take user inputs and feed them to predict directly, and the features are totally different and it always classify any instance to 1 always and but what happens is the user input, is when it predicts in real time, it did not convert it to pca, and just send to model to predict and thereby, it always predicts recurrence , even in non-recurence instances. Also, the index of the input is mismatched. nd that is why, it predicts all to one class. Please add, understood in your bid, if you have read the task. Thanks.

Django

Flask

HTML

Machine Learning (ML)

Python

ID del proyecto: 19031124

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Activo hace 5 años

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4 freelancers están ofertando un promedio de $143 AUD por este trabajo

@dinhfreedom

Dear sir. Your project attracted my attention at first glance, because I've extensive experience in PCA & Sklearn Programming. I'm really confident about your project, and very eager to join your project. If we have a chance to cooperate, I'll do my best to provide wonderful result. Looking forward to your response. Best Regards.

$250 AUD en 3 días

4,8

(58 comentarios)

6,3

@supersuntech

First:- Chatbot --> This can be integrated by any Facebook page, Slack etc. Its main aim is to reduce the human effort. For example, if this Chatbot is integrated with company page so it can easily answer you some basic questions about the company. Second:- Word Predictor --> This will be integrated with my Chatbot and it's an algorithm is such that it will learn according to previous input given and then It will suggest the next question and next word accordingly. Third:- Comment Checker --> This has a huge set of words inbuilt with its degree and level and it will analyze each comment and according to that it can give the report or if any inappropriate comment is taken it can forward to the authority. Speech Recognisation Train the database using deep learning, doing language model and lexical model for Arabic , adding functions to increase different types of noise at different levels as the picture shows. Then we notice the results.

$155 AUD en 3 días

5,0

(10 comentarios)

4,9

@ateirelbar

understood Based on my understanding of your problem, here is how I would solve it (BTW, it sounds like you already know all this, not sure why you need someone else to do it): The parameters from the PCA need to be stored (these are just the eigenvectors of the covariance matrix, but since you're using sklearn, you can use its dump/load). Then upon new data entry (real-time prediction), the PCA model should be loaded, and transform is called on it before using the trained network. It's a matrix multiplication so it shouldn't have impact on your prediction performance.

$111 AUD en 3 días

5,0

(1 comentario)

2,4

@thisismfaisal

HELLO MY NAME IS FAISAL AND I HAVE WORKED AT GOOGLE AS A MACHINE LEARNING ENGINEER I CAN HELP WITH THAT I AM NEW TO FREELANCER SO I AM BIDDING LOW FAISAL

$55 AUD en 3 días