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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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49 views

How can I predict the best treatment to give to new patient?

As part of a school project, I have to analyze a dataset with patients (with characteristics: sex, age, smoker 0/1, etc.) who received different treatments (one per patient) with a response to this ...
1 vote
1 answer
51 views

Is it possible to make an machine learning algorithm, that can outperform humans in complex games with current technology?

Would a company like OpenAi, it the "average" person be able to make a bot, using machine learning, that can outperform the best e-sport players in complex games, like PubG, with the technology we ...
1 vote
1 answer
208 views

SVM radial basis generate equation for hyperplane

I need to generate an equation for hyperplane, I have two independent variables and one binary dependent variable. Regarding this following equation for svm , $f(x)=sgn( sum_i alpha_i K(sv_i,x) + b )$...
1 vote
4 answers
365 views

How to build a model where multiple data points contribute to a result

I’m trying to figure out how to massage data and model the following scenario: Customers at a restaurant rate the quality of the service between 1-10. I have data on individual interactions between ...
0 votes
1 answer
220 views

How to classify ordered labels(ordinal data)?

I have some data similar to movie ratings and the labels are ordered, like 1 to 10. since the target label is not a nominal but ordinal variable, what types of models should I be using for classifying ...
15 votes
2 answers
13k views

Why should we use (or not) dropout on the input layer?

People generally avoid using dropout at the input layer itself. But wouldn't it be better to use it? Adding dropout (given that it's randomized it will probably end up acting like another regularizer)...
1 vote
1 answer
60 views

Using a regression model, is it possible to precisely predict "outlier" results based on a highly imbalanced dataset?

Title. I have a dataset that's highly imbalanced, say the output variable I want to predict is restricted within the range from 0 to 1, but almost all of the datapoints sit around 0.7-0.9, while my ...
8 votes
3 answers
729 views

Chi-square as evaluation metrics for nonlinear machine learning regression models

I am using machine learning models to predict an ordinal variable (values: 1,2,3,4, and 5) using 7 different features. I posed this as a regression problem, so the final outputs of a model are ...
0 votes
0 answers
14 views

Is always low bias and low variance desirable?

Assume we have two regression models M1 and M2 for a given data. Assuming M2 has lower bias and lower variance, would you always consider using this? This example shows that if the data is random ...
1 vote
1 answer
4k views

ValueError: Data cardinality is ambiguous: (Jupyter Notebook)

I'm building an OCR to read text off of water meters. I'm running into the error mentioned above when I try to fit the machine learning model. I am using the segmentation_models python library. ...
0 votes
1 answer
199 views

Decision boundary of an neural network

Starting with a). For the first unit: 0 * x1 + 1 * x2 + 1 > 0 (0, because the threshold is 0) which is the same as x2+1 > 0. For the second unit: x1 * 1 + x2 * 0 + 1 > 0 (0, because the ...
3 votes
1 answer
119 views

Need help on Time Series ARIMA Model

I'm working on forecasting daily volumes and have used time series model to check for data stationarity. However, I'm strugging at forecasting data with 90% accuracy. Right now variation is extremely ...
13 votes
3 answers
7k views

What are the disadvantages of accuracy?

I have been reading about evaluating a model with accuracy only and I have found some disadvantages. Among them, I read that it equates all errors. How could this problem be solved? Maybe assigning ...
0 votes
0 answers
15 views

What are good configs for running UNet3DConditionModel on 8 GB VRAM? (64x64x64 inputs)

What are good configs for running UNet3DConditionModel on 8 GB VRAM? (64x64x64 inputs) More specifically for this project I'm looking to use HuggingFace's UNet3DConditionModel on my home PC on a RTX ...
1 vote
2 answers
118 views

approach for predicting machine failure using maintenance history

I have been struggling with this problem for a while now and I finally decided to post a question here to get some help. The problem i'm trying to solve is about predictive maintenance. Specifically, ...
0 votes
0 answers
7 views

lost "target value" role after merge data

Hello there, Currently i am trying to learn Orange how to classify the quality of products we produce b image analysis. I have a set of images which i analyse via image embedding. This gives 1 dataset....
2 votes
1 answer
71 views

The best algorithm(s) for finding the best hyperparameters (special case)

I would like to ask for help with the following. Given the following dataset, which I have split into train and test sets: ...
11 votes
9 answers
48k views

I got 100% accuracy on my test set,is there something wrong?

I got 100% accuracy on my test set when trained using decision tree algorithm.but only got 85% accuracy on random forest Is there something wrong with my model or is decision tree best suited for the ...
1 vote
2 answers
200 views

Is it possible to extract mathematical expression of an trained ML Model?

In Python & R, Linear Regression model gives the mathematical representation after learning the training data, typically in the form of intercept, coefficients of variables, and the p-value/t-...
1 vote
0 answers
71 views

Learning from label proportions

Can someone please tell me how to implement this algorithm via this paper in simple Python as possible? I asked for code from the author but got no reply after 7 months of retrying. EDIT: Added code ( ...
1 vote
1 answer
101 views

Error when checking target: dimensions error in CNN-LSTM model for multivariate time series forecasting

I'm making a CNN-LSTM model to forecast multivariate time series: ...
2 votes
1 answer
301 views

Speed for different kernels in scikit-learn's SVM

I'm using scikitlearn in Python to create some models while trying different kernels. I was surprised to see that rbf was fit in under a second, whereas linear took a minute and poly took hours. Can ...
0 votes
1 answer
27 views

How to explain missing dates to a model?

I have this dataset that I'm trying to train a neural network on. The problem is that since weekend dates are not available, I am not confident in whether the model is able to account for that. ...
3 votes
2 answers
527 views

How to treat the undefined values which make sense?

I'm currently trying to create a few features to improve the performances of a model. One of those features that I would like to create corresponds to the difference in days between a customer's ...
1 vote
1 answer
51 views

How to measure different models' feature importance using a generic and common standard?

I want to measure the feature importance of a series of models after training them. Most models have some built-in APIs that allow me to access their feature importance, but as far as I know, these ...
0 votes
1 answer
60 views

Sale Forecasting Problem -- Is it legit to use inventory level as a feature?

I'm working on a project to predict future sales for our company's products so that the supply chain can have better idea how much to restock. Detail about the model I'm working on: Model: LGBM (from ...
0 votes
1 answer
310 views

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 ...
2 votes
1 answer
109 views

Can I forecast with discontinued data using ARIMA?

I have data for sales on monthly basis, but a few months' information is not in the CSV file or data file. Can I forecast or fill that missing month with other calculated values from present records? ...
0 votes
1 answer
163 views

K-means clustering to separate temperature vertical profiles

I have temperature measurements from weather stations in a mountainous region and I want to obtain a vertical profile from these data at any given time. In a simple case one can just plot all values ...
2 votes
1 answer
304 views

what are the next step after ML prediction and how to proceed?

I have trained an ML model with a good accuracy but what next? I am facing difficulty in answering this question, how will you present your model. Which framework do you use How do you make sure ...
3 votes
3 answers
130 views

Classification when the classification of the previous itens matter

I have a classification problem to solve, that seems to be common but I am struggling to find the name of this task and the best way to model this problem. Suppose I have a series of events that are ...
1 vote
1 answer
38 views

Fitting users' reports with joint time-semantic model

I have a historical list of reports, made by users, containing what happened (taken from a list) and the time when the report was filed. And I would like to fit the data with some joint time-semantics ...
0 votes
2 answers
99 views

Random Forest plot standardized

For a data science project, I first used a standardized scaler on data in python, ran random forest then plotted the tree. However, the values of the decisions are in their standardized form. How do I ...
0 votes
1 answer
36 views

What type of machine learning am I looking for with these column types?

I have been learning a bit about machine learning and have used a few model types (xgboost, LogisticRegression) with some test data. The more I use these models the more I realize there is a specific ...
0 votes
0 answers
16 views

Is my SPP layer well implemented on the CNN model?

Im doing a CNN model with transfer learning from a VGG16 model but Im adding a Spatial Pyramid Pooling layer on top, I have tried with different data-bases and it has worked, but I'm not sure if its ...
1 vote
1 answer
316 views

Combining multiple ranked lists

Suppose I'm given two ranked lists, A and B, with each item in the lists being associated with a score: ...
0 votes
1 answer
449 views

Multiclass semantic segmentation with some classes possibly not present in some of the images

Let's assume we have a large annotated dataset with 4 classes. In this dataset, there might be annotated images with less than 4 classes, where the remaining classes might or might not be present. As ...
0 votes
2 answers
356 views

Is there a way to make keras custom test_step aware of the call being made from model.fit and model.evaluate

I am using keras custom model with custom train_step and test_step methods overwritten. Also, have a need to change certain margin used in the loss function, only for test dataset. In other words I ...
1 vote
1 answer
244 views

Hypothesis vs Hyperplane in Machine Learning

I am finding it hard to understand the clear difference between Hypothesis and Hyperplane. I know that Hypothesis is a candidate model that maps inputs to outputs after training. And, Hyperplane is ...
1 vote
1 answer
126 views

Encoding concept for categorical data - pick one for all the columns or different for different kinds in the same df

[Beginner here] If dataset contains - both ordinal, nonordinal (few categories) & nonordinal (multiple categories > 30). Is one supposed to pick one to encapsulate of all such situations or ...
1 vote
2 answers
1k views

How to combine two different machine learning models, to get the combined result?

To further explain my question, I will explain my use-case. Say I have a model which is trained for how good/bad a food is for obesity based on its nutrition facts. And another model for, say ...
0 votes
2 answers
150 views

Every one knows data-driven modeling, but what is model-driven (or non data-driven) modeling?

There are hundreds of data-driven machine learning models. It is easy to name a few: neural networks, linear regression, SVM, etc etc... but what is model-driven (or non data-driven) modelling and ...
1 vote
1 answer
98 views

Is it possible for a feature not correlated with a dependent variable to become important in a machine learning model?

Is it possible for a feature not correlated (or faintly correlated) with a dependent variable to become important in a machine learning model?
1 vote
3 answers
4k views

How to add noise to supervised (binary-classifier)?

Note: The question is not about validating/testing a trained model. Say i have an unlabeled features set, I want to approximate the true labels (for the sake of argument lets assume it's a binary ...
0 votes
0 answers
16 views

training data of stable cascade vs stable diffusion

So according to this: https://waxy.org/2022/08/exploring-12-million-of-the-images-used-to-train-stable-diffusions-image-generator/ Stable Diffusion was trained on data from CommonCrawler. I believe ...
0 votes
0 answers
22 views

Question regarding model inference consistency

I am doing some research on gaze estimation model L2CS provided in here. When you look at the inference predictions on provided image, when face/eye direction barely changes, inference predictions ...
2 votes
1 answer
22 views

Text Classification with unlimited labels, Text Extraction?

I'm looking to use ML to read in a blob of text, and extract a name from that text blob. (The blob is from an OCR result from an iPhone) The text blob varies in size, but the name is always present in ...
1 vote
1 answer
114 views

Using Low Frequency Labels with High Frequency Features

I am trying to build a model (most likely a regression or random forest regression) for quarterly financial data. My training data has a daily cadence, but I am not sure how to work with these to ...
0 votes
1 answer
577 views

What is the best way of combining audio and visual data to make predictions?

I am trying to predict the probability of a disease by using audio and images, the audio and the images do not come from the same source. I am thinking of combining the outputs (maybe average them) of ...
2 votes
1 answer
200 views

How to retrain a K-Modes model based on daily data?

I have read that retraining a model depends highly on what you are trying to achieve. I am conscious that maybe I need to retrain my model daily and after a certain time I have to train the model ...

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