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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ValueError: Found input variables with inconsistent numbers of samples: [120, 30]

I practice XGBClassifier() to predict the target in iris dataset. here is the code: ...
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Which CNN model to use for the classification(20 classes) of gemstones (diamonds, sapphire, ruby etc) based on digital photo images and huge data set?

Im trying to build CNN Model for the classification of precious stones (like diamonds, sapphire, ruby) based on digital images. So I have data set of labeled 150,000 gemstone certifications and the ...
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Loss function for model with two-outputs

I have created a model for this Kaggle competition that outputs a classification of the level of the disease (from 0 to 4) from an image of the retina. I now want to blend the predictions for both ...
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How to do forecasting with categorical timeseries?

I have a dataset that is in the form of categorical timeseries: (specifically, we either know or don't know the values of 6 degrees of freedom of an object at any given time). If we know it, it's ...
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is there a deep learning model that handle 47800+ classes for classification?

I am trying to build a text classifier with 47893 classes and 1.3 billion (1,302,687,947) data samples. What would be the best classifier to build with such kind of data? Each data label will contain ...
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Machine learning with 2D data table and single outcome to model

I am new to machine learning and am trying to conceptualize how to effectively build a database of sports data for machine learning. I currently have a list of games and outcomes as well as separate ...
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Image parameter Regression using Tensor Flow

I have 40 data set of images of droplet that are taken at controlling parameters (F) and (V).I need to feed the images to a tensor flow network and then estimate F and V required to achieve for ...
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Do I need to use always the same "Test" dataset to compare between different models?

I have two datasources A and B, and I want to check how several methods can affect the accuracy of my multi class models: If I use cross-validation with validate dataset to obtain the best hyper ...
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Machine learning | Column names vs number when training/predicting

Been doing machine learning since a few months by now. I've a grounding questions that I couldn't answer by my self. It's possible I'm asking the wrong question: When training models, like XGBoost, ...
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Predicting student exam outcome based upon study patterns

I have a few years of data now for HE students participation in their course(es) including exam results. If I just compare formative exam results with summative results there is good correlation, and ...
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Rule based vs predictive maintenance models

I have data for pumps which have one or more sensors to record the air pressure. Apart from the sensor_id and timestamp, with ...
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How to visualize a data drift?

I want to show that my data distribution changes between data windows. Is it enough to visualize the mean and variance for every window? Is there any other solution? thank you
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How to use this data set for spatial regression?

I want to graph how much a customer spends by region and have hotspots for high spending regions. Here is an example of the csv file.
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Applying the model on validation data achieves higher performance than on test set. Is this possible?

I trained a binary cross-validated classification model and got high performance (about 90) on the test data but when I apply the model to new unseen data to see how to performs, i get even higher ...
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Should I include marginally better results in a writing sample?

I am performing some experiments and my results are only marginally better than the current state-of-the-art, 0.12% increase in accuracy but on the far side of 90's. Should I include the said SOTA ...
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Confusion matrix and precision problem

I'm trying to calculate the precision of a trained model. I have generated the right values for the true positive rate and the false positive rate. And I know that the formula should be TP/TP + FP. ...
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Looking at feature contribution after classifying groups using components

I have a lot of features and many are correlated, so I performed dimensionality reduction. I then used these components in binary classification and got high accuracy. I also performed feature ...
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Predicting probability of reaching a milestone -- How much data should I use from production universe to train/test model?

If I am predicting probability of a business to reach (x) milestone (classification 1), but the only data I have is live production data, how much of the production data should I use to train the ...
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Machine learning method to detect correlation between bike counters

I am doing a research master's degree in transportation science. I would like to develop a model for one of my classes to detect the dependence between various bicycle counters. The database I'm using ...
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Same precision, specificity and sensitivity values

My Model gives giving same precision, specificity, and sensitivity values when I'm running a loop five times to fill missing values using Random forest regression and for classification using Gradient ...
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Interpreting Learning Curves of models

I need some help to understand if the models are overfitting and which of these we can consider "the best". On the internet i only find simple examples with learning curves but in these ...
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99% accuracy in train and 96% in test is too much overfitting?

I have a binary classification problem, the classes are quite balanced (57%-43%), with a GridSearch with Random Forest Classifier I obtained the best hyperparameters and I applied the model to train ...
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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: ...
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Yolov5 model detects everything as cars

I'm facing an issue regarding my yolov5 model to detect cars. Here is the following procedure I made to train the model: Downloaded 10000 images from training car dataset (Google Open Images Dataset)....
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KMeans is not predicting the correct cluster

k-means clustering is done and created 5 optimal number of clusters. (Clustering is done unevenly). While using them in my model, the model is not choosing the exact cluster which has the exact data. ...
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1 answer
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How to train machine learning on sales forecasting problems of almost 10,000 shops?

I have a dataset of almost 10,000 shops, 'dates', 'shop ID' and 'sales amounts' as their features almost 2 years of data. I want to forecast each shop, the sales amount for 30 next days. I want to ...
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Image recognition model with CNN for face gestures is really bad

I have a dataset that contains facial expressions and their label, and I am trying to make a classification model for it. Unfortunatly, I can't manage to create a good model with CNN, as the highest ...
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What can be the reasons for 95% of samples belong to one cluster when there is 5 clusters?

'''I used the k-means algorithm to clustering set of documents which are textual data only. The document has 2lack records. Surprisingly the result for the clustering is 90% of records is storing in 1 ...
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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 ...
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I get 100% on my test set using random forest. What is wrong?

I am getting 100% accuracy on my test set when trained using random forest. Is there something wrong with my model? Code: ...
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1 answer
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How to implement linear regression

I am having difficulty achieving the same result as in sklearn while implementing linear regression model from scratch. After adjusting the learning rate, I obtained an AUC of 0.694 for this binary ...
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Ideas on how to solve a problem using machine learning

I am fairly new to machine learning. I have been in mechanical simulation field for the past 7-8 years, I realise there are potential areas which I have been doing the same thing day in and day out, ...
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1 answer
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how to evaluate the combination of tfidf and kmeans

For my nlp problem I'm using a combination of TFIDF and KMeans from the sklearn package. The tfidf gets the vectors and then I use Kmeans to cluster the texts based on the vectors. I have a few ...
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6 votes
2 answers
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Image classification architecture for dataset with 710 classes, 90,000 subclasses, and anywhere from 10-1000 images per subclass?

Been struggling with finding the best approach to handle this scenario, I'm also a novice when it comes to machine learning. I have a dataset of around 700 classes, 90,000 total subclasses, and ...
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How to predict multiple independent routes?

I have an idea in mind but, due to the lack of expertise in the ML domain, I just don't know where to start. I'd really appreciate any hints/advices on which methods to study or how to approach this ...
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The Sklearn train_test_split function is create training data and test data which are not similar

I am working on loan default data and my model is not able to make accurate predictions on the test set because the the default percentage on the test set is very different from that of the training ...
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1 answer
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How to use 5 different datasets to re-train & test your ML Classification models multiple times

My R scripts and my 5 source datasets can be found in my GitHub Repository for this project, and I originally found this source data on Kaggle. This set of source data includes 5 datasets with over ...
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Model plus client's prior recomendation

The following question is from real-life experience dealing with clients to create a certain model. So say for example I have a data set. The data set has features columns $A,B,C,D$ and labels $L$. ...
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How can i increase accuracy of my fine tuned T-5 text summarizer?

I am working on text summarization, I have fine-tuned of T-5 model with my dataset. I am using a small dataset. I have to perform with this dataset. Now I am facing two problems. 1 - Low Accuracy on ...
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1 answer
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Can applying different models and seeing which one fits best be called brute forcing?

I have seen a tutorial which said that you have to try different models and see which fits best on your data. Can this be considered brute force? I have searched this on google and the closest answer ...
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1 answer
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Create ML model from dataframe with small number of rows

I have a dataframe with 50 rows (one row for each US state), and about 20 columns with different attributes with state related data. I'm looking to build a linear regression model to predict ...
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Converting String Data to Numeric data

I want to convert String data to Numeric data as the Decision tree is only accepting numeric data. When I had Binary String data like Ever_Married[Yes/No] I converted using the ...
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Basketball-related model divided the in-sample data in half for use as two "out-of-sample" data sets. Is this an acceptable methodology?

so I'm an amateur in terms of data science skills, so I was wondering about this. I was digging through the methodology for a popular NBA player impact model called RAPTOR and came across this passage ...
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How to interpret higher RMSE and $R^2$?

I ran an evaluation on two different regression model variations using the same dataset and I am a bit unsure how to tell which model is better. The blue model has a worse RMSE of 150 and a better $R^...
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Model to recommend validation rules for each column based on the pattern of data present in the column

I have a requirement to recommend validation rules (from a set of pre-defined rules library) based on the column selected. I would like to understand the pattern of the data for the particular column ...
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Math model to predict a 2D/3D new coordinate with a finite set of 2D/3D matrix

Hope that I can describe my question well with my limited math knowledge. Imagine a gaming scenario. I have a tank that moves on a fixed-size map. And its coordinate will be sampled constantly every T ...
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` TypeError: int() argument must be a string, a bytes-like object or a number ` raised when fitting a multi input Keras model

I'm currently building a U-net model handling multiple input streams of data with Keras/Tensorflow's Functional API. Even though my model compiles, it raises a TypeError when I try to fit it. This ...
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305 views

Fine Tune GPT-3 without prompt?

I was wondering if it's possible to fine tune GPT-3 without using the "prompt" and "completion" method as shown in the documentation. More specifically, I want to fine tune a GPT-3 ...
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Should I be checking f1 score for both position labels on an imbalanced set?

I have a 3 to 1 imbalanced set. I'm using KFold for cross validation. For training I'm using RandomOverSampler to balance the training set, but the validation set is left as is. I'm testing different ...
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Lasso regression / SVM convergence CPU -> GPU

I have coded a simple supervised ML classification using 10-20K data points for 25 samples. Linear ML models run quickly for example naive Bayes, linear regression and SVM linear on a small multi-core ...
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