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.

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How to implement Naive Bayes classifier

I am working on implementing a Naive Bayes Classification algorithm. The problem requires classifying the following datasets: ...
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Using Customer Comments to predcit resturant rating

I have a list of features of a restaurant on which a customer gives a comment (from given options). I also have the overall rating of the restaurant. I would like to use this data to build a model to ...
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BERT vs GPT architectural, conceptual and implemetational differences

In the BERT paper, I learnt that BERT is encoder-only model, that is it involves only transformer encoder blocks. In the GPT paper, I learnt that GPT is decoder-only model, that is it involves only ...
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What should I visualize for humor detection model to gain some useful insight?

I was going through bunch (1,2,3) of humor detection paper. But most papers don't include any visualizations, say some graph related to model being trained. I was thinking to train some language ...
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Text Classification for columns with numbers, string and special characters

I have a dataframe with 3 columns and 1 label Here is an example of a row ...
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"No gradients" error with a black box custom layer | TensorFlow

I'm trying to create a neural network where given the pure initial state of a quantum circuit (2D-vector), it spits out 2 numbers that would be essentially fed into a quantum computer to get results ...
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Picking the right NLP model to tag words from a dataset

As the title suggests, I am posting here in the hope someone could direct me towards NLP models for tagging words. To be more concrete, here is what I wish to do. I would like to build a flashcard ...
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Fake News Detection Classifier approach

I have the dataset related to any domain like sports, entertainment, politics, etc. I just want to know that the approach I am using for fake news detection is valid or not. As I do not want to use ...
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Important features for detecting malware on the network

I am trying to build a model (Machine Learning) in order to detect malicious network traffic. At first, I am trying classify network traffic as malware or benign. After predicting the malware part, I ...
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Theoretical maximum depth of a decision tree

During my machine learning labwork, I was trying to fit a decision tree to the IRIS dataset (150 samples, 4 features). The maximum theoretical depth my tree can reach which is, for my understanding, ...
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Lower bound of confidence interval of a test data

I am interested in studying the effect of increasing data samples for a regression model on train error and test error. For this I have used confidence intervals for different values of a sample data. ...
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What ML model to train on when using an adaptive learning rate - the most recent or the one with the least validation loss?

I am currently implementing an adaptive learning rate for a neural network, meaning the learning rate gets reduced (e.g., halves) every time the validation error plateaus for 3 epochs (exemplary, ...
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What to do when your training Dataset fields for a classification model are not constant or change?

I am trying to train an image classification model by first passing training images through Google vision API to extract image properties such as color and then creating a training data set with ...
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Points to remember when embarking on an organization-wide turn to AI solutions

In our organization, we are currently in the phase of building up team, skills to automate and implement AI based solutions. So, we are very early in this AI journey. Right now, we are also working on ...
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Image-to-image ML problem: one image input and one image output

Overview I'm trying to create a model that takes a "foot heatmap" (input image) and predicts a "shell heatmap" (true heatmap). My data contains foot heatmaps with a corresponding ...
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Making predictions with limited user generated data

We've trained a ML model and deployed it to production. The trained ML model uses about 50-60 features. A user inputs set of information on our platform which is nowhere close to all the features that ...
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Why can't a multi-layer linear neural network fit this linear function data?

I am learning to implement a neural network with gradient descent, and encountered this problem, please. Using the target function ...
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save and load capsule network model?

Hi i'm working on the deployment of a trained capsule network model into web application and i have a problem loading the model in other .py file to make predictions. i tried get.config() and ...
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Are my classification results like accuracy, precision, recall etc significant and valid for general data?

So I have this data let's say of size (2000,11), and I want to do perform a binary classification based on these eleven features. There is a class Imbalance between ...
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Autocomplete dropdown and machine learning implementation

I need to develop a user interface to input demographic data from users - gender, age, location, etc. One of the fields must be a dropdown with ...
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Standardization vs min-max scaling

In the book Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 2nd Edition by Aurélien Géron, the author quoting: Unlike min-max scaling, standardization does not bind values to a ...
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Word classification

I have a task to classify the model of a product from its part number using machine learning. Part numbers can be of different lengths and forms and can contain both letters and numbers and also ...
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Augmentation for sound recognition of dog barks for CNNs

I am training CNNs to recognize dog barking, and for this I would like to augment the data sets I have (~30'000 10s clips with either barks, or no-barks in them). The straight forward idea was to mix ...
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Unsupervised learning methods

Can someone suggest me some material (links, youtube tutorials, pdf notes, ...) or some simple script in Rstudio (using maybe the iris dataset) to start studying unsupervised learning machine learning ...
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My LSTM is struck with local minima

My LSTM Accuracy is low and is the same even if I go for higher epochs. I tried varying the optimizer/changing the batch size, but it still remains the same. My data: sequence length is 300, so its ...
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Would it be possible/practical to build a distributed deep learning engine by tapping into ordinary PCs' unused resources?

I started thinking about this in the context of Apple's new line of desktop CPUs with dedicated neural engines. From what I hear, these chips are quite adept at solving deep learning problems (as the ...
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What Shape Does Naive Bayes make?

Decision Trees draw straight lines to partition the feature space. According to the Universal Approximation Theorem, Neural Networks can draw any continuous function. What sort of shape does the Naive ...
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KNN error: could not find function "train"

this is my KNN code: ...
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Weighted Voting: Accuracy and Coverage in Class Weight

I have a data set in which the data is coming from various sources. Approx 3k records were verified manually and respective source is tagged if the data comes from that source and is valid/correct. I ...
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I'm looking for some scripts or tools that can take some text, understand and generate multichoice questions, cloze deletion, pop quiz

I'm a fairly entry level coder in python but I was hoping for some guidance on if, or how I could load a block of text to generate random questions to test comprehension. My goal is to conduct a large ...
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1answer
25 views

Catboost not able to handle a very simple dataset?

This is a post from a newbie and so might be a really poor question based on lack of knowledge. Thank you kindly! I'm using Catboost, which seems excellent, to fit a trivial dataset. The results are ...
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How to extract numerical information from text descriptions

I have an attribute that is the description of an operation (i.e description of a building consent), I need to translate this to a mathematical operation. I need to find out the new number of dwelling ...
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How can I choose the best machine learning algorithms from all kinds of algorithms?

I am a beginner at data science and I’ve been learning machine learning for a while with some courses online without any help of a teacher. After I’ve got to work with some real projects on my own, I ...
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how to choose the best machine learning algorithms from all kinds of algorithms? [duplicate]

guys, I am a beginner at data science and I’ve been learning machine learning for a while with some courses online without any help of a teacher and after I’ve got to work with some real projects on ...
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Train a parametrized model to sample from a known target distribution

I wonder if there is a way to train a parametrized model to sample from a known distribution such as Gaussian. We usually don't need a model to sample from a known distribution (if we know the CDF for ...
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One-hot-encoded variables dominating clustering

I am performing some unsupervised clustering with k-means on some transaction data that contains the following information: Customer units purchased in category_1 units purchased in category_1 time ...
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1answer
29 views

Why not LinearClassifer when RidgeClassifier works?

Recently I came across this model called RidgeClassifier, It coverts the predicted value (y) to {-1,1} and then uses the Ridge Regression. During prediction if the value of y is < 0 then it is ...
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Classification issues with Binary Sentiment analysis

I am trying to conduct a binary sentiment analysis of Arabic text (i.e. either classifying social media posts into negative/positive). I built a basic dictionary that covers all words included in the ...
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1answer
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Binary Classifier , when Data Points are very less and number of features are very large

I am building a Binary Classifier. There is no Real World Scenario Problem Statement, We have just given only the data set and some guidelines. Number of features : 2040 All features are in decimal ...
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Why KNN output predicts all zeros rather one-hot label?

I have trained in supervised way several ML algorithms such as GNB,SVM, KNN. I have multi-class classification model (not multi-label). The input format has ~22 features and the output is one-hot ...
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How to use k_means algorithms on likert dataset?

I have a dataset of 10,000 customers with ten features all of which are Likert type. Like this: customer feature1 feature2 feature3 ID1 3 1 5 ID2 4 5 4 ID3 3 5 1 ID4 1 3 2 ID5 2 5 1 ID6 1 3 4 ...
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65 views

Soft actor-critic reinforcement learning for 100x100 maze environment

I am doing a project which requires a soft actor-critic reinforcement learning agent to learn how to reach a goal in a 100x100 maze environment as the one below: The state space is discrete and only ...
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how an autoencoder denoise an image

i am using denoising autoencoder to denoise the image in the unsupervised way.But still after implementation of the denoisng autoencoder i am unable to understand how an autoencoder network know which ...
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9 views

What is a good few-shot classifier function?

Is there any pre-written library or function which can receive a few examples of data values being classified and then extend that to new data values received?
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How to monitor PSI with model like LGBM, XGBoost?

In order to monitor or calculate PSI, I need to have bins of different features. However, in case of tree model, features value in training sample are continue values, I wonder if I require to call <...
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1answer
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Visualizing outliers using T-SNE

I'm trying to visualize outliers in my data using T-SNE and it seems like the outliers appear as three different clusters. The original data has 7 different columns but I chose to plot the outliers on ...
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Model KNN: error unused arguments

I write a KNN model and my R script is: ...
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6 views

How to inference LTR (Learning-to-Rank) models?

I've recently started looking into LTR models such as RankNet and LambdaMart. In the instance of LambdaMart and the LETOR dataset, I believe the model accepts the following as training input: query_id ...
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How can i adapt accuracy metric for multiclass classification?

I have a problem which is multiclass e.g. That is 4 classes. I would like a custom metric to assess the model where only if class 3 is predicted as class 2 and class 2 is predicted as class 3 (i.e. ...
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KNN model with two classes in the train dataset and three in classes in test

I have a dataset like this: ...

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