Questions tagged [machine-learning]
Machine learning provides computer algorithms that automatically discover patterns in data and make intelligent decisions from them.
240
questions
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0answers
25 views
To scale or not to scale in regression and classification algorithms
I'm a new DS student, and I get the basic concept of Standardisation, whilst I was learning we used StandardScaler in some algorithms, and not in others on the same dataset, and I'm still confused as ...
0
votes
0answers
27 views
Fuzzy Matching Optimizations and Score Punishment Ideas
Introduction to the problem
Hey everyone,
I have started working as an intern, and my first project is to come up with an implementation of company names matching. Customers send a form with the ...
1
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0answers
46 views
Logistic Regression for Fashion MNIST T-shirt vs. Shirt
I wrote a Logistic Regression for Fashion MNIST to classify T-shirt vs. Shirt.
here is the class
...
2
votes
0answers
41 views
xagents - implementations of reinforcement learning algorithms
Description
It is valid to say, this work started and evolved from a standalone DQN implementation, which I included in an old question, to a mini-library xagents, housing 7 re-usable tensorflow-based ...
0
votes
0answers
33 views
Implement the XOR Gate using a 2-layer neural net with just Python & NumPy
I wrote a 2-layer neural net with just Python & NumPy to implement the XOR Gate, here is the code
...
1
vote
0answers
36 views
The best tensorflow neural net I got so far for iris dataset
Compared to my another post Logistic Regression for non linearly separable data which uses one-layer net, i.e. Logistic Regression to classify the iris data set, this post is to discuss the tensorflow ...
0
votes
1answer
26 views
Logistic Regression for non linearly separable data
Iris Data Set consists of three classes in which versicolor and virginica are not linearly separable from each other.
I constructed a subset for these two classes, here is the code
...
0
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0answers
55 views
Logistic Regression for MNIST binary classification
I wrote a Logistic Regression model that classifies MNIST digits.
I used tensorflow & keras only for import the dataset.
...
0
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0answers
5 views
Ratio of intra-class scatter by inter-class scatter is getting minimised by linear discrimination process
This question is complicated (at least for me who is new in machine learning and image processing).
I need help in understanding, why my iterative process is minimising the ratio of inter-class ...
2
votes
0answers
18 views
DQN implementation
I just wrote my pong DQN. It seems to work. I'm looking for a performance based review on anything that might slow down the training in complex models.
main.py:
...
0
votes
0answers
17 views
Predicting with multiple independent hot-encoded variables
My attempt at multiple linear regression.
I am trying to make a qualified guess about a user's rating of a movie, through machine learning. I am new to this, so my judgement isn't the best. And I am ...
2
votes
2answers
67 views
Updated version of my first neural network in c++
I got lot of suggestions for optimizing my neural network last post I made, now I wanted to post updated version of it were I got rid of most of performance eaters, now I would really appriciate ...
8
votes
3answers
682 views
My first functional naive neural network in C++
I just wrote my first standard neural network with SGD gradient descent in c++, I am really interested if I have done anything wrong or inefficient, suggestions would help me a ton
(There is lots of ...
0
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0answers
20 views
Logistic regression using Sklearn in Python
I'm trying to learn how to use logistic regression with Sklearn. After learning the theory, I tried implementing it using the Heart Attack Analysis datasheet from Kaggle.
Here's a snippet of the data:
...
2
votes
1answer
100 views
a prototype of finding the (almost) best learning rate and initial weights so that a perceptron converges with the minimal iteration
First of all, I chose the nearest data points/training examples
...
2
votes
1answer
63 views
A simple clusterness measure of data in one dimension using Java - follow-up 2
(See the previous version here.)
This time, I have encorporated all the suggestions made by Marc. Also, I changed the type of points from Double to ...
1
vote
1answer
47 views
A simple clusterness measure of data in one dimension using Java - follow-up
(See the previous version here.)
(See the next version here.)
This time, I have incorporated all the suggestions made by Roman; my new version follows.
...
7
votes
1answer
56 views
Optimize K-Mean for large number of clusters
I am writing a Python code for KMeans clustering.
The aim of this post is to find out how I can make my below mentioned code optimal when the number of clusters is very large. I am dealing with data ...
0
votes
0answers
31 views
Keras: Using Autoencoders for prediction
I have a dataset which I divided into two sections horizontally. Column A of first section is the input variable and Column A of second section is the target variable. I am trying to build a Denoising ...
9
votes
4answers
2k views
C++20 : Simple Softmax classifier for MNIST dataset
I wrote a simple softmax classifier to classify MNIST digit handwriting data set. Feel free to comment anything!
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0answers
20 views
Stacking Classifier Implementation
I was going through the book Hands on Machine Learning With Scikit-Learn & Tensorflow. In one of the chapters, the author mentioned ...
3
votes
1answer
82 views
Pandas replace rare values in a pipeline
A common preprocessing in machine learning consists in replacing rare values in the data by a label stating "rare". So that subsequent learning algorithms will not try to generalize a value ...
1
vote
0answers
46 views
validation and test loss for a variety of PyTorch time series forecasting models
Hi everyone I'm trying to reduce the complexity of some of my Python code. The function below aims to compute the validation and test loss for a variety of PyTorch time series forecasting models. I ...
0
votes
2answers
44 views
Machine Learning Program
I've written a program that finds the difference between data and gives output.
Here's the code:
...
1
vote
0answers
105 views
Model Pipeline to run multiple Classifiers for ML Classification
As a general rule of thumb, it is required to run baseline models on the dataset. I know H2O- AutoML and other AutoML packages do this. But I want to try using Scikit-learn Pipeline,
Here is what I ...
0
votes
2answers
188 views
Multithreaded implementation of K-means clustering algorithm in Java
Hello I have written a multi-threaded implementation of the K-means clustering algorithm. The main goals are correctness and scalable performance on multi-core CPUs. I expect to code to not have race ...
2
votes
0answers
42 views
Looping over files to create a dataframe
As part of my NLP project at work, I want to loop over all files that are either PDF of docx in the same directory. The end purpose is to create a dataframe with text content of the files in one ...
2
votes
0answers
32 views
Optimize binary classification model
I've created binary classification model from scratch, just to understand intuition behind that.
However when I compare my implementation to model from tensorflow/pytorch with the same parameters and ...
1
vote
0answers
21 views
Industrial Practices for Time-Series Forecasting
Hi I have wrote a code here for predicting temperature across months. This is the dataset that I was using: https://www.kaggle.com/sumanthvrao/daily-climate-time-series-data
I have used a SARIMA model ...
0
votes
0answers
224 views
Convert JPG to H5 and plot the images
I'm learning ML/DL and found the process of getting the data and labels quite tedious. There is not much details on how to get JPG files into H5, which is (afaik) the only way to work smoothly later ...
2
votes
1answer
73 views
Calculation of the Distance Matrix in the K-Means Algorithm in MATLAB
Purpose of the code :
To assign the corresponding label of the centroids to the points which are close to it. Below is a graphical (2D) example.
Variable X is a matrix, rows represent the points, ...
3
votes
0answers
22 views
Transfer learning CNNs for image classification in TensorFlow
This code works, and I'm pretty sure it's mathematically/algorithmically correct:
...
2
votes
0answers
17 views
Implementation of Policy Gradient Reward Design paper
I've implemented the first experiment from the Reward Design via Online Gradient Ascent paper. I don't have any specific concerns, but it's my first time using multiprocessing or doing reinforcement ...
3
votes
0answers
293 views
Playing pong (atari game) using a DQN agent
I trained a DQN agent using tensorflow and OpenAI gym Atari environment called PongNoFrameskip-v4, but this code should be compatible with any ...
4
votes
0answers
70 views
Using VAE for reconstructing images
Article: https://arxiv.org/pdf/2009.07047v1.pdf
Full Code: https://colab.research.google.com/drive/1KZZuIa7Lk13ImZLJ3b-kxMfcveOPaWvN#scrollTo=XhdMfBFtzaEH
Dataset: https://drive.google.com/file/d/...
1
vote
0answers
68 views
Implementing Convolutional Neural Network
Context
I was making a Convolutional Neural Network from scratch in Python. I completed making it .... It works fine ... The only thing is that it takes a lot of time as the size of the input grows.
...
4
votes
2answers
161 views
C++ performance: Linear regression in other way
Here is the code that can be used for calculation of mathematical function, like ax^2 + bx + c.
It is fast enough if you choose small length, otherwise if ...
1
vote
0answers
49 views
How to handle overfitting in Random Forest
I have a random forest model I built to predict if NFL teams will score more combined points than the line Vegas has set. The features I use are Total - the total ...
2
votes
0answers
25 views
Data Visualization (rendering env)
How can I improve this code? It renders a ML env with openAI gym and matplotlib. I am new to coding so not sure if my variables or format or any lines can be improved.
...
1
vote
0answers
50 views
How to speed up this numba based decision tree?
In order to improve the performance of this code fragment, I have speeded up some code fragments by using the numba. However, a frustrating thing is that the performance of this decision tree is bad. ...
10
votes
2answers
272 views
Convert an English sentence to German using Bahdanau Attention
Context
I am following this tutorial .
My mission is to convert an English sentence to a German sentence using Bahdanau Attention.
Summary of the Code
I first took the whole English and German ...
2
votes
1answer
98 views
A Tiny Nearest Neighbor Classification Implementation in C#
I am practicing to implement the KNN classification tool in C#. The basic point structure is constructed by the class Point, and there are two members in ...
4
votes
0answers
151 views
A Very Simple Support Vector Machine with SMO Algorithm Implementation
Context. I was looking for some simple implementation of SVM with the SMO algorithm that can be used as an in-class problem together with a simple mathematical explanation of how it works.
The problem ...
10
votes
1answer
286 views
K-means function in Python
I have written a k-means function in Python to understand the methodology. I am trying to use this on a more complex dataset with a larger value for k, but it is running super slow. Does anyone have ...
1
vote
0answers
25 views
Machine Learning Implementation when dealing with high variance data
I'm am trying to classify MLB (Baseball) games whose score go over the total based on the total and the number of people who have bet the over. The total is a number set by Vegas and a bettor can ...
6
votes
1answer
768 views
Simple neural network in c++
I have implemented a neural network in C++. But I'm not sure whether my implementation is correct or not. My code of the implementation of neural networks given bellow.
As an inexperienced programmer, ...
5
votes
0answers
64 views
Machine Learning Implementation
I am new to ML and I wanted to implement a Linear Regression to predict a golfer's scores based on certain feature supplied to my model. I would like a review to see if I'm implementing this correctly ...
2
votes
1answer
179 views
Smart Tic Tac Toe, a reinforcement learning approach
I'm currently familiarizing myself with reinforcement learning (RL). For convenience, instead of manually entering coordinates in the terminal, I created a very simple UI for testing trained agents ...
4
votes
1answer
140 views
C++: k-Nearest Neighbours with Lambdas and Priority Queues
I implemented getting the \$k\$-nearest neighbours of an origin point to a set of points in C++17. I tried to use some more modern C++ lambda techniques and was looking for feedback on use of lambdas, ...
5
votes
1answer
166 views
C++ - Logistic Regression Backpropagation with Gradient Descent
I implemented binary logistic regression for a single datapoint trained with the backpropagation algorithm to calculate derivatives for a gradient descent optimizer.
I am primarily looking for ...