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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Automatic legal document reviewing advice

I am lawyer from SK. I also like programming and Maths. Which technology should i use for this task? Automatic legal document reviewing. I have a big data set of specific contracts in slovak. Now I ...
0 votes
1 answer
25 views

When applying softmax over multiple dimensions of a tensor, does the order in which those dimensions are matter?

Lets say i have a tensor of order 256, dimensions indexed from 0 to 255. Lets say i am writing a function implementing the softmax operation because i am a newbie and i want to understand the ...
1 vote
1 answer
62 views

Sustain learning separately - continuous learning

This question is to seek suggestions on how to architect the continuous learning approach in distributed manner. Let me explain the situation: In my classification problem, I have classes which can ...
1 vote
1 answer
15 views

Reduce mode searching behaviour of VAE

I'm applying VAEs to sections genomic data (haplotypic vcf format, so binary variables), with one model being trained on each section. They each have different layer sizes and weights to better fit ...
3 votes
1 answer
323 views

Finding dominating attributes with in the clusters generated

I am having a dataset of customers where each customer is represented as some feature vector and I am applying K-means algorithm to this dataset. On the basis of those features, I can abstract and ...
2 votes
1 answer
70 views

How to do a Multilabel classification where the label order is important?

I am new to machine learning and I hope I used the right term in the question. So I am doing carbon composite modelling for my college project, and each composite sample are created by stacking ...
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1 answer
139 views

Categorical data preprocessing for training a algorithm

I have a training dataset where values of "Output" col is dependent on three columns (which are categorical [No ordering]). ...
1 vote
1 answer
78 views

Is reinforcement learning suitable for the Dial-a-Ride problem?

Is reinforcement learning suitable for this problem or will it perform poorly against classical algorithms? "The Dial-a-Ride Problem (DARP) consists of designing vehicle routes and schedules for ...
2 votes
1 answer
249 views

How to use a Multinomial Naive Bayes Classifier on different sets of data?

I am working on a sentiment analysis project involving tweets. I used a Kaggle dataset to train my model for sentiment analysis and want to use that trained model to predict the sentiment on an ...
1 vote
1 answer
282 views

Building a prediction model for dynamic coordinates and later categorize as binary classification

Project Summary I have a website (academic project) that records mouse movements such as click, mouse up, mouse down, etc. It records the coordinates for each event on a given web page from a visitor....
0 votes
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15 views

Trying to train a denoising autoencoder to restore missing information from a binary image

I am building a denoising autoencoder to repaint lanes from a binary image. The input is a binary image that has incomplete lanes, due to vehicles getting in the way. I repaint the lanes manually so ...
1 vote
3 answers
86 views

What could be the problem leading to the result that a model can never perfectly overfit?

I tried to fit my model on a small batch of 128 samples for binary classification. The model should be powerful enough as it has hundreds of thousands of parameters. It should be able to overfit to ...
2 votes
1 answer
151 views

How Does Cross-Entropy Work With Softmax Activation Function?

I found online that the derivative of a cross-entropy activation function with a softmax activation is (output - expected), which had me very confused. If for example, the expected value is 1, and ...
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19 views

Question on theory from original GBM article

I am reading the original gradient boosting machine article and, maybe because my statistics are a bit rusty, have a few questions on one section. In section ...
2 votes
1 answer
72 views

Estimating location in a model

I have a big dataset with 10 columns and about a 100,000 rows. Each 5 rows represent a person being tracked and the data related to this tracking such as time, velocity, etc. the last two columns are ...
0 votes
1 answer
127 views

The Impact of TV Advertising on Website Traffic

I need to build a model that measures the impact of TV advertising on website traffic. I have two datasets: one contains the number of visits to the page and a timestamp, the other contains a ...
1 vote
1 answer
601 views

Will repeatedly fine-tuning on new data cause overfitting?

I have a binary classification model which I have trained on a training set. On the validation set its accuracy is ~85%. I set up early stopping which ended training when validation loss increased. ...
0 votes
0 answers
8 views

Understanding the code for calculating the 95% confidence interval of AUC using bootstrapping

It's really embarrassing, but I lack statistical knowledge. I would like to find the confidence interval for AUC at 95%. Actually, I got the code from here(https://stackoverflow.com/questions/52373318/...
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0 answers
9 views

input problems of using LSTM in python to forecast future value

There are two columns rainfall data and water level in my dataset and I want to predict the water level based of the past values using LSTM on python. My problem is do I need to include the past ...
0 votes
1 answer
19 views

Question about contextual embeddings?

How do BERT and RoBERTa generate contextual embeddings? The articles I've read keep saying that transformer encoders work bidirectionally. Because of self-attention, they can look at every token, ...
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2 answers
5k views

Dimension Mismatch Error during dot product in Python

I have two matrices user_vecs and item_vecs I am trying to take the dot product of the two to build a recommendation engine: The ...
0 votes
0 answers
20 views

How to predict inside of the box temperature at a give outside temperature using python?

I Need help predicting inside of the box temperature at a given outside temperature. Background I have a system (also known as a BOX). The BOX is insulated from the outside environment and contains ...
1 vote
2 answers
137 views

Build a predictive model for number of hockey goals in a season for an individual player

I'm looking to build a predictive model for hockey players individual statistics. My goal is to predict how many points a player can be expected to have at the end of the season. To do so, I thought ...
0 votes
0 answers
11 views

Stream response from custom RASA actions to the chatbot

I am using RASA PRO with CALM. I was thinking of using openai api within a custom action and stream the streaming response coming from openai to my chatbot. Openai is giving me streaming response and ...
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0 answers
13 views

graph neural networks for molecular embeddings

I want to extract the embeddings from various graph neural network designed for small molecules. I want to know does the model need to be trained to do the same. Or should be extract the layer in ...
0 votes
2 answers
936 views

How do I replace NaN values using group by pivot_table in pandas DataFrame?

I am working on a machine learning practice problem, from https://datahack.analyticsvidhya.com/contest/practice-problem-big-mart-sales-iii/#ProblemStatement I want to replace the null values in the ...
1 vote
2 answers
698 views

Graph Neural Network fails at generalizing on unseen graph topologies

I'm using PytorchGeometric to train a graph convolutional network for regression over nodes problem (the graph models physical phenomena in the network of sensors; the network of sensors is actually ...
0 votes
1 answer
65 views

Input Tensor Shape for CNN Binary Classification of Time Series Data

I want to predict whether a machine will fail based on the most recent set of measurements taken by on-board sensors. I have several dozen machines, each with a sensor that takes a measurement at ...
3 votes
1 answer
145 views

Output value of a gradient boosting decision tree node that has just a single example in it

The general gradient boosting algorithm for tree-based classifiers is as follows: Input: training set $\{(x_{i},y_{i})\}_{i=1}^{n}$, a differentiable loss function $L(y,F(x))$, and a number of ...
1 vote
2 answers
105 views

Need help to increase classification accuracy for classified ads posting

I have to predict the category under which ad was posted using the provided data; I cannot gain accuracy more than 74% for my model. I am not sure what I am missing. What I have done so far: Cleaned ...
0 votes
0 answers
7 views

Training split generation - Extremely Slow

I am fine-tuning mbert on wikipedia dataset, loaded with Datasets (Hugging face) ...
1 vote
1 answer
304 views

Input Normalization for Transfer Learning

If I am training a deep neural net with input features that are physical in nature (e.g. temperature, precipitation, etc), and I want to be able to perform some kind of transfer learning where I train ...
0 votes
0 answers
20 views

Questions about the process of feature selection through feature importance

'Shap feature importance' was obtained through xgboost, and variables with the lowest feature importance were removed one by one from 50 variables until only 1 variable remained. As a result of ...
0 votes
1 answer
392 views

How to get weightage of each factor for a prediction in a neural network classifier?

I am working on a model to predict which employee is going to resign from a firm. The dataset has columns like Date of Birth, Date of Joining, Department, Gender, Marital Status, Years at company etc. ...
0 votes
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11 views

Is it necessary to average the shap values ​that have been processed through cross validation?

Is it necessary to average the shap values ​​that have been processed through cross validation? I saw a post in Towards Data Science that calculated the shap value through 10 CV and then averaged it. ...
0 votes
0 answers
16 views

Does hours spent training early in an Associates career impact the amount of revenue they generate in the future?

I can use some help with project design and choosing the correct method to answer this question. I have a dataset that contains associate ID, associate specialization, hours worked, revenue, period, ...
1 vote
1 answer
197 views

How to cope with new/unseen targets classes in incremental learning algorithms

According to scikit-learn documentation, the sklearn incremental learner itself may be unable to cope with new/unseen targets classes. Is there any available python machine learning library which ...
4 votes
2 answers
231 views

What is a "shot" in machine learning?

I keep on hearing this term "shot" used in machine learning. Is a "shot" well-defined? From what I can tell, "shot" is a synonym for "example". Most machine ...
0 votes
1 answer
302 views

AttributeError: module 'graphing' has no attribute 'histogram'

I want to make a histogram plot, after importing the library called graphing it gives me an error even when it has been installed. ...
2 votes
1 answer
205 views

ROC_AUC score is higher before tuning n _neighbors for KNN

This is for multiclass classification. Before tuning the n_neighbors for KNN, these were the results: ...
0 votes
0 answers
6 views

Collaborative Filtering Using Multiple Features

I am looking to create a recommendation system for content. The content can be likened to an instagram post (contains a caption, hashtags, an image, etc.). I want to use user-based collaborative ...
0 votes
1 answer
280 views

Incremental learning on Autoencoder for anomaly detection

I want to incrementally train my pre-trained autoencoder model on data being received every minute. Based on this thread, successive calls to model.fit will incrementally train the model. However, the ...
1 vote
1 answer
99 views

Exogeneous, Endogenous Variables in Structural Causal Model

https://en.wikipedia.org/wiki/Causal_model#Definition Wikpedia defines causal models as: an ordered triple $\langle U, V, E\rangle$, where $U$ is a set of exogenous variables whose values are ...
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19 views

Pipelines in SKLEARN

I am building a pipeline. I am downloading a dataset from an online ML repository and generating descriptive stats for it. The link for the dataset is https://archive.ics.uci.edu/dataset/45/heart+...
1 vote
1 answer
279 views

How to detect the begin word and end word in a sentence with machine learning

I have some English text that has been tokenized. For example, the length of text token is about 20000 and each word (tokenize) has an index. Also, each index has a label, as the beginning word in a ...
0 votes
0 answers
21 views

ML Methods For Modelling Latent Variables

I have some time series predictor variables, $\{\mathbf{X}_t\} = \{\mathbf{X}_0, \ldots, \mathbf{X}_n\}$, and some other time series data $\{\mathbf{Z}_t\} = \{\mathbf{Z}_0, \ldots, \mathbf{Z}_n\}$. ...
0 votes
1 answer
30 views

As a result of cross-validation, the difference between the ideal auc values ​of the train set and the test set

In the attached figure, the x-axis is the number features of s removed, and the y-axis is the average auc score over 10 CVs. I want to choose the point with the highest score while avoiding ...
0 votes
3 answers
77 views

Machine learning and time-based data

I want to predict conversion rates for an eCommerce store. I have data from Google Analytics with features like averageSessionDuration, bounceRate, numberOfVisitorsBySource etc. and the corresponding ...
0 votes
0 answers
25 views

I have a poor understanding of nested cv and generalization

I'm not sure if I understand the purpose and generalization of 'nested cv' correctly. I found information online that the purpose of nestd cv is to be able to correctly estimate generalization error. ...
1 vote
1 answer
608 views

Predict items customers would buy in next order

I am working on a time series classification problem to identify what items customers would buy in their next order (customers orders different products every week). Let's say we have a customer who ...