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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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1answer
20 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 ...
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1answer
25 views

a baseline ML model

I do not know how to interpret the concept of a baseline ML model. "Before spending months cleaning data, establish exactly what you want to use that data for, and establish a baseline ML model ...
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AQI prediction using machine learning [closed]

Air quality index can be calculated using formula? Why are we using machine learning algorithms to predict AQI?
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Pruning Model Weights in Tensorflow 2

I am currently trying out things with the Tensorflow model optimization library with the goal of reducing the sizes of models that are run in our production Tesnorflow Serving containers. This project ...
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10 views

predicting average time with regression

I have a trip duration dataset that looks like this: I want to use other parameters to predict the waiting time (wait_sec). The waiting time refers to the time the vehicle is stuck in traffic or so. ...
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1answer
22 views

Why is linear regression not doing worse with a low weighted attribute?

I've been able to build a few linear regression models that can predict a material strength quite well: minimum RMSE of 17.95 using 11 attributes that I have selected from 159 original attributes. The ...
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1answer
35 views

What does my learning curve indicate?

I have performed logistic regression. And I am getting an accuracy of 77% with my current model. I divided my training set into cross validation set and train set. And I plotted a learning curve (...
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17 views

Guidance for creating a machine learning model for math equation solving

I do not have any experience with machine learning and have come to need a ML model for this use case. Using an already existing ML model I am able to extract the formula to calculate charges from ...
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ValueError: Input 0 of layer conv_lst_m2d_60 is incompatible with the layer: expected ndim=5, found ndim=4. Full shape received: (None, 7, 7, 512)

I am building an anomaly detection model using keras upon videos. There are total 179 frames. The original dimension of each frame is given below: ...
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What model to use for relative comparison between 3 figures?

I am working on a problem where I am given three images of different dishes (A,B,C) and the task is to figure out if figure B or ...
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2answers
25 views

Can a machine learning model be used as some kind of compression?

I'm trying to understand how machine learning is working. I read a lot and now came into my mind that it could be missuses in a practical way. I also hope that this question is on topic here. Please ...
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51 views

Machine learning algorithms for suggesting new baby names [closed]

https://www.lexalytics.com/lexablog/machine-learning-natural-language-processing https://towardsdatascience.com/named-entity-recognition-ner-meeting-industrys-requirement-by-applying-state-of-the-art-...
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Iteratively improving ML model on a small dataset

I have a spam classification model which I created using a very small dataset.I have exported it as shown ...
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Determine most important features in diagnostic data

I have a dataset of device diagnostics. I have two tables: one relating each device to failures code. Two devices can share a failure code for example a common chip malfunction. The second table links ...
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For Incremental Learning ML Model do we have to perform any kind of label encoding?

Please guide me on Online / Incremental Learning ML model, I am using Creme tool for my hands-on, where as my dataset has some categorical features, I did tried to do encoding but still getting error ...
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1answer
34 views

How to double audio dataset?

I am trying to develop a mispronunciation detection model for English speech. I use TIMIT dataset, this is phoneme labeled audio dataset. A phoneme is any of the perceptually distinct units of sound. ...
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1answer
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Can anyone help with me how to train new data with already saved pickle file? [closed]

Can anyone help me with the code me to train new data with already saved pickle file? I've trained the model with RandomForestClassifier from sklearn and saved the model into .pickle Now I'm trying to ...
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1answer
35 views

Emotion Recognition with Multi-task Learning [closed]

Introduction I am a beginner in Data Science and currently working on a learning project aimed at emotion recognition from a bio-medical sensor dataset. The dataset consists of 8 sensors data from 20 ...
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1answer
18 views

How does epochs related with converging the model?

I have read on Internet that epochs is used to give the time for the model to converge but I don't know how ? . I was thinking that epochs is used because to train the model sufficient times . How ...
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0answers
12 views

How to explain a figure to highlight importance of features

I have got this figure by calculating feature importance in my models (test set). As shown in the figure (it is edited but it should be ok for this example), values are very very low (less than 0.025)....
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What techniques are there to train custom sentence classification models with reasonable memory footprint?

We are currently working on tasks that involve user-inputted data (e.g., question-answers, short-answer-grading), with a framework that will allow them to be improved through active learning. However, ...
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How to train an ML to predict improvement in patient recovery?

I am interested in training an ML model that would predict improvement in a patient's injury. Assume doctors have collected two sets of MRI images from hundreds of patients who have suspected brain ...
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15 views

Why is my Celcius to Kelvin Model performing so bad compared to my Celcius to Fahrenheit Model

I am new to tensorflow and I saw an example model which was made as following - ...
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15 views

How can I get accuracy of a predicted value specifically in Python?

I am currently working on a disease prediction machine learning model. I used Random Forest Classifier in my model, and now I am trying to get probabilities or accuracies of predicted values, but the ...
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0answers
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Multi Input Network MNIST-CIFAR10

I have the following task of meta learning: We want that our neural network learns to sum weights. 1)Do the training on MNIST, and on CIFAR10 (as support dataset). We want that performance (accuracy) ...
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2answers
45 views

ideal algorithms to demonstrate overfitting or underfitting

When one tries to look up concepts such as overfitting and underfitting, the most common thing that pops up is polynomial regression. Why is polynomial regression often used to demonstrate these ...
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1answer
28 views

How to force a NN to ouput the same output given a reverse input?

I want to choose an architecture that can deal with an input symmetry. As input, I have a sequence of zeros and ones, like [1, 1, 1, 0, 1, 0] and at the output layer I have N neurons that outputs a ...
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2answers
148 views

Alternatives with better GPU than Google Colab Pro

I am currently running/training MAchine learning models that are very GPU expensive, Google Colab Pro is not giving me enough GPU/RAM Is there any alternatives with better GPU and more RAM than ...
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1answer
37 views

Exploration in Q learning: Epsilon greedy vs Exploration function

I am trying to understand how to make sure that our agent explores the state space enough before exploiting what it knows. I am aware that we use epsilon-greedy approach with a decaying epsilon to ...
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15 views

Encoding entities with features of continuous values

Given a set of entities, I would like to predict the next in the sequence; for this purpose, I would like to use RNN. However, my first challenge is how to model the entities. A possible input ...
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12 views

Prediction ability by small sample size datasets

All the datasets i have for modelling are relativ small - ca. 80 rows and there is no way how to increase the sample size. If there is no significant or dominant parameter / input (usually there is ...
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1answer
37 views

Why we take $\alpha\sum B_j^2$ as penalty in Ridge Regression?

$$RSS_{RIDGE}=\sum_{i=1}^n(\hat{y_i}-y_i)^2+\alpha\sum_{i=1}^nB_j^2$$ Why we are taking $\alpha\sum B_j^2$ as a penalty here? We are adding this term for minimizing variance in Machine Learning Model. ...
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1answer
12 views

Train and predict two labels in a single process

I have a python program that makes predictions using scikit-learn RandomForestClassifier. The label is called "default" and it's the default status of a ...
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0answers
45 views

Creating a new feature from an existing one using decision trees

Is it possible to create a new feature out of two, or more than two existing features using a decision tree? If so, how, and can it produce features with good information value that can better help ...
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1answer
18 views

Can you choose a binary feature matrix for a binary classification model

This may be a stupid, but, I am new to deep learning (and machine learning for that matter) and I can't seem to find any literature to help with my question. All I can see when Googling many different ...
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1answer
35 views

Which ANN structure to use?

Let $\mathcal{S}$ be the training input data set where each input $u^i \in \mathcal{S}$ has $d$ features. I want to design a ANN so that the cost function below is minimized (the sum of square of ...
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1answer
34 views

How to explain a relationship between Accuracy and F1 Score / F-Measure?

I am building a CNN model for pitch estimation using a song recording. Pitch estimation is done by inputting spectrogram to CNN model and make the CNN predict pitch sequence (250 pitch values per ...
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1answer
24 views

What is the meaning of the bubbles / spikes in the shap values ​plot?

Here are an example of shap values plot from here. How to interpret the 'bubble' or 'spikes' on this shap values plot I highlighted in yellow color?
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26 views

Gaussian Mixture Implementation and Optical Recognition of Handwritten Digits Data Set

Trying to implement Gaussian Mixture model implementation in python using the Optical Recognition of Handwritten Digits Data Set which consists of 10 training folds each of size $\left[100x64\right]$, ...
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1answer
17 views

Is there a good deployment module using Golang's amazing single binary compilation model?

From my limited understanding, it's quite annoying trying to deploy models like PyTorch. So one would need something like ONNX. But another approach like Golang with a single binary is VERY attractive....
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1answer
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How to best accommodate snapshots of data over time into a single dataset for training

Say we have customers who acquire or not a product, and we have snapshots of the customer's profile monthly, with the information if at that given month they acquired or not (binary label). I have two ...
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24 views

RandomForest (RandomForestRegressor) returns weird predictions

I wish to see how different algorithms perform when predicting stocks (using technical indicators as features). When modeling the randomForest (and looking at the graph) I get very bizarre results. ...
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0answers
55 views

Find VC dimension

I'm studying theoretical machine learning at university, and I have this problem in textbook, that I have no Idea how to start. In space $X=R^2$ are given two models $H_1$ (rectangle with sides ...
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1answer
38 views

Should I make single machine learning model for predicting price of house or 6 different models, given 6 datasets for different cities? [closed]

I am currently working on "Housing Prices in Metropolitan Areas of India" (kaggle dataset), with 6 different csv files for 6 different cities. All have same columns (40). Working on a real ...
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How do PoseNet identifies the key points of human pose estimation?

PoseNet is a deep learning TensorFlow model that allows you to estimate and track human poses by detecting body parts such as elbows, hips, wrists, knees, and ankles , It uses either MobileNet or ...
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Which Machine learning Algorithm would work best in predicting particle size distribution (PSD)?

Im a beginner with machine learning and data science. i am working on a project where i have to work with an algorithm/ machine learning model that would predict the particle size distribution ( a ...
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1answer
18 views

How to improve machine learning model using 2+ datasets

I am building a supervised machine learning model which (for example) predicts heart failure (yes/no). I have two datasets from 2 different labs A and B, which both have decent distribution, aka it's ...
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1answer
28 views

Prediction Algorithm for Data with high Randomness

I have data for the orders of the previous year containing the product and the seller who sold the product. I have an information product, product category, seller, delivery address price etc. ...
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1answer
26 views

Deep neural network models merging

Recently I am working on the neural network deep learning algorithms, just curious to ask is it possible to merge two neural network models and to output one model that contains all the learned ...

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