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classification-algorithm

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awesome-graph-classification
awesome-gradient-boosting-papers

🎨 Color recognition both on a webcam stream in real-time, on video and on a single image using K-Nearest Neighbors Machine Learning classification algorithm is trained with Color Histogram Features.

  • Updated Dec 21, 2019
  • Python

Identification of trends in the stock prices of a company by performing fundamental analysis of the company. News articles were provided as training data-sets to the model which classified the articles as positive or neutral. Sentiment score was computed by calculating the difference between positive and negative words present in the news article. Comparisons were made between the actual stock prices and the sentiment scores. Naive Bayes, OneR and Random Forest algorithms were used to observe the results of the model using Weka

  • Updated May 18, 2020
  • R
Lactem
Lactem commented Sep 29, 2019

It would be beneficial to have more thorough descriptions of what each part of the program does internally, even if it's at a high level. This would especially make sense for the examples portion so that people can know what exactly it is that they're looking at. Maybe we can compile our knowledge here and then format it nicely in the examples README? We can also include non-essential / lower-leve

fksontini
fksontini commented Mar 22, 2019

Traceback (most recent call last):
File "C:\Users\f.ksontini\AppData\Local\Programs\Python\Python37\lib\site-packages\language_check_init_.py", line 594, in get_server_cmd
cmd = cache['server_cmd']

C:\workplace\IA\ML-fomo>python main.py 'Metallica' 100
Traceback (most recent call last):
File "C:\Users\f.ksontini\AppData\Local\Programs\Python\Python37\lib\site-packages\language_ch

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