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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version control for code and output models

I have a question about version control for both code and the models it generates. We are developing ML models that often involve hyperparameters and so we might do many runs with different ...
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straight line or going down

I want to cluster data points based on the pattern ( six points each )so if it is going down or straight line or going with ups and downs! do you have any ideas how can I achieve it accuratly, I tried ...
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peer-reviewed articles and restriction on the code availability

My background is a PhD in Earth Science. I recently joined a private company which developped an algorithm to perform climate analysis (R based). I have been asked to apply this algorithm to a case ...
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New client's future profits prediction

Problem: I want to evaluate the efficiency of new clients' acquisition. For that reason I want to be able to forecast the profit generated by client (in let's say 12 months from acquisition month) and ...
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Detection of unloadings by GPS coordinates

I have a history of the car's movements, a list of GPS coordinates with timestamp (in GPX format). I'm new to ML, tried to solve but doesn't work well. I have several problems: How to correctly ...
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Remove frame from background

I am having 400 images that look like the following: I would like to remove the frame and only get the image in the middle: I tried the MODNet model ...
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datatypes as input in machine learning algorithms

I have a dataset and I am trying to perform binary classification by using different machine learning algorithms I have seven columns as input where all are int64 except of one that is float64. So my ...
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1answer
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AutoML for categorical feature encoding

I have an input dataset with more than 100 variables where around 80% of the variables are categorical in nature. While some variables like gender, country etc can be one-hot encoded but I also have ...
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exclude variables with no variation during prediction?

I am working on a binary classification problem. I do have certain input categorical variables such as gender, ethnicity etc. ...
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Overfitting? Is it ok, if I've met my desired threshold?

I've trained a lightgbm classification model, selected features, and tuned the hyperparameters all to obtain a model that appears to work well. When I've come to evaluate it on an out of bag selection ...
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name 'layers' is not defined

I am trying to use EfficientNetB7 from keras implementation Image classification via fine-tuning with EfficientNet but always the following code gives me error: ...
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How can I plot the covariance matrix of scikit-learn's Gaussian process kernel?

How can I plot the covariance matrix of a Gaussian process kernel built with scikit-learn? This is my code ...
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what are the effect on machine learning regression model if the dataset has two exact same columns

What will be the effect on the Machine learning model if the dataset has two exact same columns(exact 1 correlation). One thing that comes to my mind is that if two columns are exactly the same then ...
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Accessing regression coefficients when using MultiOutputRegressor

I am working on a multioutput (nr. targets: 2) regression task. The original data has a huge dimensionality (p>>n, i.e. there are far more predictors than ...
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1answer
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Imbalanced data set with Sample weighting - How to interpret the performance metrics?

Consider a binary classification scenario whereby the True class (5%) is severely outbalanced to the False class (95%). My data set contains numeric data. I am using SKLearn and trying some different ...
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How to use rule-based labelling intelligently?

I have a dataset like below The outcome column is labelled as positive if the % difference between target final Qty and ...
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1answer
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Custom Named-Entity Recognition (NER) in product titles using deep learning

I am new to machine learning and Natural Language Processing (NLP). I am trying to identify which brand, product name, dimension, color, ... a product has from its product title. That is, from 'Sony ...
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Why is my extremely simple neural network code performing so badly?

first time poster here. I am trying to build a NN using sklearn MLPRegressor on a file which has the shape (1024,3). The first two columns are two dimensional input data, the third is the target. ...
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How to Find the Next Moves of Cars From Given First Moves?

I want to find next moves of cars from the previous moves, but I could not figure out what should I use as algorithm. Can you help me to find a way to solve this problem? I have a lot of car data like ...
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How to recognize this type of pattern in my data?

I have this question that is just bugging my mind and I can't find an actual solution to it online. I have a certain pattern I would like to detect in my data, like the example I have in my picture, ...
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Detecting Data Drift in Audio Data

For a give set of audio files collected from an industrial process via a microphone, I have extracted suitable features and fed them into a neural network for training a binary classifier as depicted ...
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1answer
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Advice / Good practises | CNN poor image diversity

I am currenty working on a project that involves multiple cameras fixed on the ceiling. Each time I take a picture, I check whether there is a "cart" right under the camera. I would like to ...
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How do you optimise BPNN with PSO?

In the context of prediction, how would you optimise a backpropogation neural network with particle swarm optimisation?
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1answer
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learning curves of a classification algorithm

I a trying to understand this learning curve of a classification problem. But I am not sure what to infer. I believe that I have overfitting but I cannot sure. Very low training loss that’s very ...
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Ideas to enforce uniformity of error in linear models

I am looking for ideas to not only solve the least square problem, but to enforce errors to be roughly similar. One idea I had is to add the variance of errors in the classical Ordinary Least Square ...
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Can t-SNE be applied to visualize time series datasets

I have multiple time-series datasets containing 9 IMU sensor features. Suppose I use the sliding window method to split all these data into samples with the sequence length of 100, i.e. the dimension ...
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Using Raspberry PI as a remote classifier

I am currently looking for similar projects to use a Raspberry PI as a classifier. I want to run a service on the microcontroller permanently, so that the model is loaded only once and then waits for ...
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How Can I Estimate the Full Path Route of an Aircraft From a Given Halft Path?

I have a lot of real data of aircrafts paths which starts from the departure airport and ends on the arrival airport. Each aircrafts data is a time series of points like below: Point(lat, lon, ...
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is there a way to compare two k-prototype models performance?

i try to understand which of my two k-prototype models to use both models contains the same categorical features one of the models contains a bit more numerical features in other words is there a ...
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Difference between Doc2Vec and BERT

I am trying to understand the difference between Doc2Vec and BERT. I do understand that doc2vec uses a paragraph ID which also serves as a paragraph vector. I am not sure though if that paragraph ID ...
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How to show prototype of output before building model

Currently in my work, we are working on a POC for a AI project. We intend to do a binary classification using traditional classification algorithms. However, my boss wants me to show a feel of the ...
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How to gps data anomaly detection in python

I have gps format dataset lat, lon. I want to detection anomaly using python. I tested knn, smv, cof, iforest using pycaret. But i did not. These colors anomlay because the angle change is too much ...
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1answer
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Transform multi-class problem to multi-label problem

I found this question but I need an answer to the other direction. Example: Let's say we want to predict if a person with a certain profile wants to buy product A and/or B. So we have 2 binary classes ...
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1answer
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Estimate timeline for a ML Project

I am a novice data scientist and have been asked to provide an estimate for a data science project in our organization. From the problem stmt description, i am able to understand that it is a ...
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How can I use Wikipedia2vec model for embedding my article named entities as 40% entities are not in a wikipedia?

I have news articles in my dataset containing named entities. I want to use the Wikipedia2vec model to encode the article's named entities. But some of the entities (around 40%) from our dataset ...
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Any way to make NER tagging with float(2.0) and inferencing with str(2)

One of the NER attribute is tagged with float (3.0, 2.0, ...) while the text file I am trying to inference from are in string format of (3, 2, ...). The Spacy model I used can't pick up the numbers ...
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Where can I get audio datasets? [closed]

Pls I need help I am supposed to curate dataset for depressed and undepressed patients Audio dataset I really don't know how to go about it Pls do u have any idea how I should do it?
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Constructing circular towers to show that single hidden layer feedforward neural networks can approximate any continuous function

In this intuitive explanation of why wide-enough shallow feedforward neural networks can satisfy the universal approximation theorem from any continuous function on a compact domain, the author uses, ...
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2answers
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How to categorise customer complaint using NLP

I have a dataset of community complaints and I would like to build a NLP model on those descriptions and tag a category (can be referred for an inspection or Not ie "Not referred) to each of them....
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Machine Learning resources

I'm not sure if this is the right place to ask this question, but is there any online source that provides a complete in-depth explanation of Machine Learning algorithms, all at one place, but not too ...
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LSTM advantages

Can someone briefly explain what does this (bold) mean: LSTM is well-suited to classify, process and predict time series given time lags of unknown size and duration between important events. Thank ...
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1answer
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Interpreting 'values' of a Decision Tree

I am trying to interpret my decision tree here which was resulted as a part of pre-pruning- I am trying to understand why the values in my nodes are in decimal places. Ideally, they should represent ...
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Does every column need to be np.log?

I have questions regarding data cleaning for machine learning. Let's say my dataset has three columns with different skewness For example: label column skewness = 1.500, feature column 1 ...
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Find train sample with features distribution similar to test

Assume that I have two datasets $Train$ and $Test$. And there is the problem illustrated below: there are different feature distribution between two datasets I want to find the train subset $A \...
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Variational Autoencoders VS Transformers

I'm relatively new to the field, but I'd like to know how do variational autoencoders fare compared to transformers?
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Feature scaling on null values

How to handle null values in dataset for performing feature scaling on a particular column? i.e.Should we keep the null value as it is or impute some other value? Is there any tutorial on how to ...
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How can you predict the amount of each expression of the dependent variable for given independent variables?

The starting position is the following: There are categories 1 and 2, as well as features A, B and C. A representation would look like this: What is a way to not only predict the occuring categories (...
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Sentence Classification Machine Learning API

Are there any ML models or APIs that can be used to classify a sentence into one of the four types of sentences; i.e. declarative (statement), imperative (command), interrogative (question) and ...
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Evaluate clustering labels using classification

I've clustered 500 documents into 7 groups using K-means. Is this reasonable to use classification models to evaluate the clustering model? What I would do is to get these 500 labelled documents using ...

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