Questions tagged [machine-learning-model]

A machine learning model is a simplified representation of a dataset, derived from statistics in the data, used to make predictions. It can represent patterns, behaviours or features within this dataset which have been learnt by the algorithm during training.

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Likert Scale Target Variable

I have a case study where the target variable (a single factor) gauged through multiple items. the items are measured using 5-Likert scale (Never, Seldom, Sometimes, Often, Very often, Always) since ...
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What is the best way for me to classify this audio data?

I have a set of audio data. I would like to classify each audio file based on a half-second of data from a give time period. The audio data is given as counts as a function of time $s(t)$. Right now ...
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How to calculate a trend to use as a feature in a machine learning model?

In a machine learning model one of the features is unemployment: ...
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Predict the next 10 minutes using ML

I want to predict if there will be a goal in the next 10 minutes of a football game given current match stats. The dataset is unbalanced so I tried to undersample the most popular class with ...
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Can Shapley values be used with a simple passthrough model to evaluate real-world data as a model, but without an actual model?

I currently run many of the ML models I keep through Shapley Additive Explanation (SHAP) values. I am curious about analyzing a raw dataset using SHAP values. Why shouldn't I be able to construct a ...
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Classification problem with too many classes and requiring specific outputs

I'm trying to solve this exercise in which I have around 10 thousand rows of data with 6 columns of features and one column with over 3 thousand targets. The problem says I need to program an ...
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Model from an aggregate

I’m in a place where we’re unable to train models on data due to GDPR. What I want is to predict people getting a job (y) given (x,x,x,x…) their employment type working full time or part time, work ...
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Is it possible to get by month simulations in orbit?

I am looking to use Uber's Orbit (https://uber.github.io/orbit/) to get time series predictions. By default, orbit will output point estimates with prediction intervals defined by the user. What i ...
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Accent on special words or characters can affect machine learning algorithms?

Good evening, I wanted to ask this question about the accent in words or special characters can affect machine learning algorithms. I'm looking to do a job. I would like to know a recommendation for ...
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Is there a machine learning tool that works directly on databases?

Is there a database that can work with machine learning directly? I do not want to use Python or R to build my machine learning pipelines. Is there a database that does this natively?
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SGD performing better than Adam in Random minority oversampling, I don't know what is the reason. Help

So my dataset image before and after balancing looks like this: But when I train with Adam(0.0001) and SGD(0.0001), the results are very different. Why? What is going on under the hood? This is ...
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Is it a good idea to retrain ML model on new observations with labels predicted by model itself?

in the company where I work we retrain ML models regularly every day. Now we started to experiment with retraining a model by new observations with labels predicted by model itself. I've tried to ...
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Evaluate best model [duplicate]

Let's assume I have 2 models Model 1: Train Accuracy = 92.4% Validation Accuracy = 37.6% Test Accuracy = 35.3% Model 2: Train Accuracy = 37.0% Validation Accuracy = 34.2% Test Accuracy = 34.1% ...
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Why does my mean average precision metric show as 0.000e+00?

I have an object detection model with my labels and images. I am trying to use the tensorflow ranking metric for MAP, https://www.tensorflow.org/ranking/api_docs/python/tfr/keras/metrics/...
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Training and validation accuracy extremely low for Autonomous Lane Navigation via Deep Learning

Using a SmartCar running on RPI4 i collected all the images necessary for training. Training is done using CNN Nvidia's Model with Tensorflow and Python. Took about 900 Images for Up and 800sh for the ...
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Clustering on Market-1501 dataset

I am trying to perform clustering on the Market-1501 dataset. The approach that I am using is as follows: I train a Person-Reid Model (using this repository: Reid-Strong-Baseline) Use a version of ...
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Queries on architecture of production pipeline for a batch predictions

I have a Problem statement to predict Expected delivery time (in days) and below is the information we have from client. Prediction to be batch inference. Each batch inference to have millions of ...
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Should I use validation data and val_loss when training final model?

I am training a keras model that utilizes early_stopping in order to prevent overfitting. This requires that I set aside a validation dataset. My task requires that ...
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Keras MultiHeadAttention layer: Dimension value must be integer or None or have an __index__ method, got value 'TensorShape([None, 6, 8])'

I am running into a lot of trouble trying to use Keras MultiHeadAttention. My model: ...
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how to keep correspondence between ROI and background of a particular image during feeding them as input to a network

I am working on a CNN. I would like to provide the cropped object (object of interest in an image) and its corresponding background as the input to the CNN. So, how can I provide a specific background ...
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Gaussian Process Regressor with sample weights

I want to train a Gaussian Process Regressor with the possibility to specify the sample weights. In particular I'm facing a problem where I need to study the uncertainty provided by the GP, but at the ...
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neural network return the same output

I am trying to train a neural network for regression to predict an output (regularization parameter) of size 1 (it should be positive). I normalized the data then I shuffled it. I used 3 hidden layers ...
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Guidance in finding the correct neural architecture / design and type of network for a complex forecasting model

I've spent the last few weeks catching up on the ML topic and I believe to have a pretty good grasp on the basic concepts. I know how to use Pytorch for simple univariate forecasting, I know how to ...
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what kind of algorithm should I use to classify the text data example given?

What kind of classification or learning algorithm that suits this kind of data example If I have to build a model using the given key words then predict column B and then to column A? what kind of ...
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LassoCV model training with 150+ features

I'm trying to fit a dataset of about 150 features using LassoCV. Right now I'm using this loop to try and find the best value for alpha (get_tts is just a function to retrieve test/train sets): ...
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corresponding class labels of two unsupervised learning algorithms

I am working on a time series clustering problem. I made two models (hierarchical tree) with different pre-processing techniques using this class in package dtaidistance: ...
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1 answer
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How can I improve my current model to get a higher mAP value? (Stuck at 79~78)

I am facing an issue trying to improve my model for object detection, this is something which I have been facing for quite a few days. I have tried to improve my model by fine tuning and also changed ...
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How to solve Nonlinear least squares problem?

Initial idea is to use euclidean distances. But I do not understand how should I solve this task.
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how to describe a situation with very low F score

I have trained a classifier using Keras Convolutional LSTMs. The curves are as follows. can someone describe what happened to this model? and why for a while the F1, precision, and recall became ...
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Customer Propensity Model Data Preparation, How to handle new customers?

I'm preparing a customer propensity model. I have five years of historical data. I plan to use a window of three years, i.e. customer behaviour for the last three years is used for predicting whether ...
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Where do I draw the line at unbalanced datasets?

I have a problem where I am to construct a classification variable Yes/No based on another feature's value. We are interested in the Yes class in this case. I am told to use 10-fold cross validation. ...
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GNN Model - Analyzing Training Curve

Introduction. Actually, I am working on a Graph Neural Network (GNN) model to predict some graph-level float values. So, input=graph, output=float predicted value. I trained and evaluated the proposed ...
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Method of calculating sample size for a machine learning model [duplicate]

Is there any method of calculating sample size for a machine learning model/problem?
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why we have problem with gradients when feature values are of different range?

A blog below mentioned. " Because different features do not have similar ranges of values, gradients may take a long time, oscillate back and forth, and take a long time before they can finally ...
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Multi-Output or Mult-Task Learning - Regression

ALl! Problem Definition: I have a dataset consisting of N samples (consider them 2D images), and there are K continuous output values(Y1, Y2, Y3, ...) for each sample. Actually, it is a regression ...
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Running a simple onnx model on Jetson Xavier DLA

I have a simple python script which I am using to run TensorRT inference on Jetson Xavier for an onnx model (Tensorrt version 8.4.0 + cuda 11.4) I want to run this inference purely on DLA available on ...
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Loading a model saved in s3 to SageMaker instance

I trained a ML model in SageMaker using Docker Container. After the training is finished, the model is saved as .pkl file which gets written to S3 bucket as .tar file. I need to use that model to run ...
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Article extraction from newspapers

Currently I'm working on a task that involves having a page of a news paper and putting bounding boxes around each individual article.The first approach I thought of was using visual features to ...
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Adding a human insights into the Vehicle Routing Problem (VRP)

I have the following setting: Every week a similar VRP is solved, this solution is sent to the handler. The handler makes some changes to the suggested solution based on business knowledge (school ...
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How to convert machine learning XGBoost "R" binary model into CORE ML on iOS Swift?

How can we convert our sleep stage classification "R" XGBoost binary model on Windows into CORE ML on iOS to run model on iPhone? CORE ML doc says it inputs XGBoost -- need guide or tutorial....
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Formal conditions on mappings that can NOT be learned from data

I am new to machine learning and would appreciate some help on the following question. I have observed the literature is focused on algorithms, how one learning does better compared to others for a ...
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Freight Matching ML Algorithms

Has anyone worked on Carrier Freight Matching machine learning algorithms for logistics industry (digital freight matching)? If yes i need help to understand what type of algorithms worked best for ...
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How to Predict Probabilty that the Customer will buy specific Product?

We have data consist of previous transaction history consisting of Date,Order-id, Product-id, Product name, ordered or not. We need to predict a specific product probability for all the customers that ...
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Newbie in ML - Using error traces to predict issues

We have trace data from Jaeger which shows end-to-end information about requests/transactions/error codes. Jaeger UI/APIs are useful in debugging issues after they have happened. The requirement is to ...
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Can I use different dataset when performing model stacking?

Let's say I want to detect new species of fish. I have several models, each trained to recognize a different characteristic, e.g., the speed of known fish, the size of known fish, their known shapes, ...
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What methods I could use to analyze the contingency table?

I am data science beginner, and I have a question about methods that I could use to analyze the following data. It is a simple case, I am trying to check the influence of cohabitation before marriage ...
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Supply chain model

Looking to build a supply chain model. This would include weather data, shipping data, supply and demand levels. Ultimate goal is to predict price using such a model. Any ideas on how to develop ...
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Is there practice to train language-to-code transformer (multi-modal transformer) using uni-modal pretrained models-transformers?

Language-to-code transformation/generation require multiple skills - language and reasoning skills to digest the core problem from the natural language specification. And programming language ...
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Autoencoder general questions and poor loss

I'm trying to get a simple autoencoder working on the iris dataset to explore autoencoders at a basic level. I'm running into an issue where the loss of the model is extremely high (>20). Can ...
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Random Forest Generating Bad Predictions: What might the issue be?

I'm using sklearn's RandomForestRegressor to try and model a relationship that involves three Feature variables (x1,x2,x3) and ...

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