Questions tagged [machine-learning]
Machine learning provides computer algorithms that automatically discover patterns in data and make intelligent decisions from them.
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Time Series Forecasting
I'm currently working on a project involving time series analysis and have written the following code for the train-test split section. I'm particularly concerned about the correctness of the ...
user284332
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Low Validation and Test Accuracy with Random Forest on ECG signals
I'm working on a project involving ECG data classification using a Random Forest model. Unfortunately, my model's performance is significantly lower than expected, and I'm struggling to understand why....
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A machine learning model for predicting bit strings in Java
I have this GitHub repository (BitPredictor.java). Basically, I tried to harness a machine learning model for predicting bit strings. I have implemented it to the best of my understanding and have ...
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Pytorch code running slow for Deep Q learning (Reinforcement Learning)
I'm a new student in reinforcement learning. Below is the code that I wrote for deep Q learning:
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Python sklearn rolling yearly validation
I am trying to implement a simple modelling pipeline with rolling c.v., making use of the TimeSeries split. The code is provided below with a working example dataset. (please don't pay too much ...
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Matrix Factorisation class packaging methods for factorisation of explicit & implicit data matrices using Gradient Descent, SGD and ALS
Attached below, and also as this GitHub gist, is code for a Python class I wrote as part of a personal learning/portfolio project on collaborative-filtering recommender systems via matrix ...
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Making sklearn's decision trees easier to traverse
scikit-learn's decision tree structure is difficult for me to navigate. I would prefer to have functionality like tree.left, ...
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Minimal AlphaGo algorithm implementation for game 2048, connect4
I'm writing tutorial code to help high school students understand the MuZero algorithm. There are two main requirements for this code.
The code needs to be simple and easy for any student to ...
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Custom neural network implementation in TensorFlow to compare normalisation vs. no normalisation on data
I am performing a sports prediction multi-class classification problem, and wanted to compare the differences in model performance between normalised and non-normalised data. You can see the 2 ...
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Machine learning training, hyperparameter tuning and testing with 3 different models
I am trying to solve a multi-class classification involving prediction the outcome of a football match (target variable = Win, Lose or Draw). With a dataset of 2280 rows, which is 6 seasons of ...
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Keras Tuner Subclass for Time Series Cross-Validation
Custom Keras Tuner with Time Series Cross-Validation
I have written my own subclass of the default Keras tuner Tune class.
Objective: I needed a way to incorporate ...
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Convolutional Neural Network (CNN) in Julia
I wrote an n-dimensional convolutional neural network from scratch in Julia (check out the GitLab repo or the GitHub repo). It implements the following layer types:
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Efficiently computing a batch of results given a batch assignment vector and series of corresponding matrices
I have a 1D tensor of tokens that belong to different batches. The batch sizes here are uneven. Each batch needs to be multiplied with a corresponding weight matrix. My current approach is using a ...
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convolutional neural network in python
I am new to python, so the challenges for me currently are:
Clear, simple code, trying to follow standard practices
Useful comments,
Use types (for better understanding of input/output relationships.)...
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Design an algorithm to predict words based on a skeleton from a given dictionary
The model I'm building first selects a secret word at random from a list. The model which uses an API then returns a row of underscores (space separated)—one for each letter in the secret word—and ...
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