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Questions tagged [machine-learning]

Machine Learning is a subfield of computer science that draws on elements from algorithmic analysis, computational statistics, mathematics, optimization, etc. It is mainly concerned with the use of data to construct models that have high predictive/forecasting ability. Topics include modeling building, applications, theory, etc.

4 votes
1 answer
174 views

I am trying to implement the strategy of hierarchical classification with chained classifiers and a Bayesian network, as in the paper of Serrano-Perrez & Sucar. The data in my case are ontologies, ...
Anisa B.'s user avatar
  • 129
1 vote
0 answers
13 views

I have a problem in which I'd like to try to approximate an unknown function using the a specific version of the Kolmogorov representation theorem. I will have somwhere between at minimum dozens of ...
richarddmorey's user avatar
2 votes
0 answers
20 views

Given there are so many kaggle competitions, how does the winner win technically? Does he/she invent a completely new algorithm to solve the problem? By now there are 8 million sincere students who ...
ANKIT CHAKRABORTY's user avatar
6 votes
2 answers
303 views

What is the standard method for splitting time series into train/validation/test in time-series forecasting? Example 1000 time series and total time steps is 300. Forecast horizon is at time step 200 ...
cdt123's user avatar
  • 141
5 votes
1 answer
30 views

I recently scraped a large dataset from several websites and ended up with around 25–30 potential features that might influence the target variable. The dataset is fairly large (hundreds of thousands ...
WorksBuddy's user avatar
2 votes
0 answers
15 views

The documentation is a little bit confusing so I thought I would ask here to make sure, I'm using: ...
cdt123's user avatar
  • 141
7 votes
4 answers
336 views

if I have the binary matrix which looks something like this (this is only 10 rows of binary matrix, I have a dataset of a million rows, so you can see what the binary matrix looks like): ...
machine_learning_student's user avatar
1 vote
0 answers
81 views

In the contest of binary graph classification, we were thinking about considering the last layer features (before the outputs) of a GIN (Graph Isomorphism Network) and concatenate them with the ...
Filippo Portera's user avatar
5 votes
0 answers
30 views

I have build and trained a NMT model using Rnn in Google colab and Now when I am trying to predict for my test data my Google colab session keeps on crashing . The shape of my test data is 47838×55 ...
swar_codes's user avatar
4 votes
1 answer
43 views

I have a target with skewed distribution. So, i tried applying TransformedTargetRegressor from scikit using np.log1p as the function and np.expm1 as the inverse function. However, when i evaluate it, ...
Ocean's user avatar
  • 745
6 votes
1 answer
129 views

I'm learning about classification using decision trees. I'm using DecisionTreeClassifier function in the scikit-learn library in Python to train the model on training data (yields fully grown tree), ...
aweller3's user avatar
1 vote
0 answers
181 views

This is my first time posting here I'm a beginner in Data Science and currently trying to apply what I've learned to a real-world problem. I built a web scraping script to collect statistics from ...
Felipe Reis's user avatar
5 votes
1 answer
120 views

I am working on a movie recommendation problem where I get multiple files from the source, and the total data size is around 900 MB. I am using the ...
RushHour's user avatar
  • 259
0 votes
0 answers
37 views

I am working on a major project titled Utilizing Satellite Data and Deep Learning to Monitor Agricultural Vulnerabilities to Climate Change. My goal is to develop a system to monitor agricultural ...
Shivani Toorpu's user avatar
2 votes
0 answers
48 views

I am trying to build a solution to detect a particular sound against all possible other sounds occuring in nature. My approach is to train a One-Class SVM only on my class of interest, hoping it will ...
Antoine101's user avatar

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