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.

Filter by
Sorted by
Tagged with
0
votes
0answers
6 views

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 ...
0
votes
0answers
5 views

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 ...
0
votes
0answers
16 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 ...
0
votes
1answer
24 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. ...
0
votes
1answer
23 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 ...
0
votes
0answers
16 views

CNN Model Seems To Just Be Guessing

I am working with a binary classification problem, and regardless of what changes I make, the model seems to just be guessing between 0 (Negative) and 1 (Positive). The dataset is imbalanced at a ...
4
votes
1answer
180 views

How can precision be less than one in Leave-One-Subject-Out binary classification if each subject contains only one class

Say I'm trying to classify a medical condition. Theres only two classes: Sick and Healthy. I build a model and I can't split the data because I don't want data from the same patient being in training ...
0
votes
0answers
14 views

Why the prediction of this Random Forrest model is so poor in this machining dataset?

I am using Random Forrest to predict the MRR (Material removal rate). But the predictions have been quite off the mark. Even Linear Regression gave a much better result. I don't know where I'm going ...
0
votes
1answer
24 views

Prevent model from over-focusing on strong features

I have a classification model (DNN/Linear layers with some transformers and other things later). The input to the model are several different modalities of different lengths and different amounts of ...
0
votes
1answer
20 views

Why is shuffling timeseries a bad thing?

I'm trying to understand precisely why it is a bad idea to shuffle time-series when splitting train and test data. Like, what is false about shuffling time-series? How does it tamper with the model?
0
votes
0answers
10 views

Selecting which categorical variable optimizes a target variable?

this is my first question here! I am working on developing a machine learning model that can select which NFL play type (pass, run, punt, or kick) will optimize win probability added based on a ...
0
votes
0answers
10 views

Which checkpoint file to be used as starting checkpoint for retraining the model in Machine Learning?

I kept a Tensorflow Object Detection model on training to identify diamonds in an image. While training, checkpoint files are saved in Trainings folder. Checkpoints ...
1
vote
1answer
24 views

Classification algorithm that only matches trained examples

I have 10 categorical features and a multi-class target. Training data contains rows where the same 10 categorical features may map to a different target class. What classification algorithm should I ...
0
votes
0answers
11 views

estimating single or multiple model for Multiple Time Series Forecasting

I am a newbie in the ML field. So please, neglect or better correct, if I am wrong somewhere. I am working on a requirement where details of loading time for each page/component will be given. Now I ...
0
votes
0answers
9 views

Learning a and predicting workflow for a certain goal

I am trying to come up with a strategy which could learn a workflow for various goals and then based on some input goal, predict the workflow which could fulfil the goal. Goals are achieved by ...
-1
votes
1answer
14 views

Understanding features vs labels in a dataset

I am in the process of splitting a dataset into a train and test dataset. Before I start, this is all relatively new to me. So, from my understanding, a label is the output, and a feature is an input. ...
1
vote
0answers
27 views

Can we combine decision tree , xgboost , lightgbm to make one hybrid classifier? [closed]

Can we combine three different classifier to make one hybrid classifier ?
1
vote
0answers
18 views

Reinforcement Learning reward is not converging to zero

I am new to reinforcement learning. I am trying to build an RL algorithm which will predict cloud hardware capacity required for an org in terms of compute, storage, memory. The algorithm which i have ...
1
vote
0answers
27 views

How can I compare a NN model and a linear regression?

I have a small dataset (1500 rows) and to predict the imbalanced target, I am running two linear models (linear regression and lasso) and one nonlinear model (Neural Network) on it. I am using Area ...
0
votes
0answers
16 views

Use Large Existing Dataset to Extract Information From Text

What I have: I have a large dataset of documents and their data. So I have the text of about 1M documents, and I know, for example the invoice number, of each one. What I need: Is there a way to use ...
0
votes
1answer
30 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
0answers
12 views

Trying to input a list of strings into my LSTM model

I'm training a model for dialogue act classification. I'm trying to write it so that I can enter a singular list of strings and receive a prediction for each of the strings. I've come to understand ...
0
votes
0answers
17 views

How to find out if someone cheated by training on the test set?

Do approaches exist to see if somebody (e.g. authors of a scientific publication) unfairly improved their results by using (parts of) the test set also for training? Any ideas? Using a new and ...
2
votes
0answers
16 views

What algorithms can handle probabilistic targets?

I have a classification problem where I want to want to use probabilities instead of classes to train my model to learn to output probabilities. In my dataset, I have instances where the probabilities ...
0
votes
0answers
13 views

Weighting training data from time-series

I want to evaluate whether or not it is feasible for me to train a machine learning model using sample data that I can acquire. I have many time-series, and I am able to establish groups of 'related' ...
0
votes
1answer
26 views

Why is my CNN not training

Hi I am trying to train a CNN to differentiate between pictures of dogs and pictures of cats. It does not seem to learn anything no matter how I change the architecture. I have used the following code ...
2
votes
1answer
40 views

How to handle highly Imabalanced classification?

I have been dealing with a classification problem. Real issue is the imbalance here I have ~500,000 -ve samples and ~300 +ve samples.End result is predicted probabilities NOT hard 0-1 classification ...
0
votes
1answer
23 views

Training CNN: Understanding number data generated while training the model

I am training CNN on kaggle and my training and test datasets shapes are as follows: ...
1
vote
1answer
28 views

Confidence score for all observations is between 0.50 - 0.55

Hello Data Science Stack Exchange Community, This question will appear to be open-ended, however any answers or thought will be much appreciated. I am trying to go-through a pre-trained Random Model ...
1
vote
0answers
15 views

How to model the unknown in data science [closed]

I have been asked this question in interview which I was not sure how to respond. Situation: My company provides personal loans where consumer income is minimum $10,000 per annum and we have data to ...
0
votes
1answer
25 views

100% Accuracy on test dataset using a previous developed model oputput

My dependent variable is a probability that is sourced from someone else's classification model. I am using this probability as a dependent variable as I don't have the actual data. On building an ...
2
votes
0answers
14 views

Validation set after hyperparameter tuning [duplicate]

Let's say I'm comparing few models, and for my dataset I'm using train/validation/test split, and not cross validation. Let's say I'm completely done with parameter tuning for one of them and want to ...
0
votes
0answers
13 views

How to classify hierarchical feature?

Assume that I have this data set (a taxonomy of parent-child features) ...
0
votes
0answers
17 views

Machine learning terminology (method, model, architecture, task, objective)

I got a bit confused about the usage of machine learning terminology in books / papers / discussions that seems somehow not completely consistent to me. Therefore, I want to know if you would agree ...
0
votes
0answers
15 views

Python: None Values when executing model.fit()

I am working with CNN project to classify a sequence of pitch. The pitch class has a total of 51 classes, meaning I want to classify 51 pitches available in a dataset. For the metrics, I plan to use ...
0
votes
0answers
10 views

How to prepare/optimise data for FP-Growth algorithm

I'm using spark mllib for FP-Growth algorithm for our ML model. Description of my issue: I have taken transactional data from our production database to mine the frequent brought items recommendation. ...
1
vote
0answers
7 views

How to build a simulator for a physical machine given a set of datapoints of its behaviour?

I have a database with millions of datapoints describing the behaviour of a heat pump. For every second, I know various temperature, pressure, mass flow and power measurements as a response to the ...
0
votes
1answer
22 views

Why does my model learn with Ragged Tensors but not Dense Tensors?

I have a string of letters that follow a "grammar." I also have boolean labels on my training set of whether the string follows "the grammar" or not. Basically, my model is trying ...
0
votes
1answer
33 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 ...
0
votes
0answers
22 views

Invent first, find its use later

The typical pipeline in ML is Find a data-related problem that you want to solve Build a model or algorithm that feeds on data related to the problem to try to solve the problem Check if the solution ...
1
vote
1answer
16 views

Which metric to use for evaluating a rating system

I have a system which gives a star rating of the quality of work(on scale of 1-5, 1 being extremely poor and 5 being exceptionally good). An expert labelled a test set with their ratings of quality of ...
2
votes
0answers
51 views

flexibility vs complexity vs number of predictors in machine learning

I'm new to machine learning so am quite confused with the above concepts. It seems to me both flexibility and complexity measures how well the model fit the data (in terms of the curvy-ness), so what'...
1
vote
0answers
10 views

multi-observed features [closed]

I am working on a ML model where individual features may have a highly variable number of observed values. The model will predict a continuous variable so I am planning to use a Regressor. More ...
3
votes
1answer
58 views

At what stage are ROC curves used when building machine learning model?

When developing a machine learning model, at what stage are ROC curve with AUC used? Typically I have three data sets train - ...
1
vote
1answer
28 views

Remove correlated features before or after splitting test and training set?

I want to remove highly correlated features before training my classifier. I am wondering if I should do this before or after splitting the test and training set. I don't immediately see how doing it ...
-1
votes
2answers
19 views

What is the name of this basic machine learning example?

Some time ago I was reading a book on machine learning in which they had an example that would take some data and try to determine based on weather, temperature, humidity and Wind if a sports team ...
1
vote
2answers
28 views

Update machine learning model while retaining the prediction results exact for old data

New to ML here. In our industry, we are looking for a type ML method/model that can be updated to accommodate new data points while keeping the prediction value of the historical data exactly the same....
2
votes
1answer
11 views

Will images modification get me a better machine learning model?

Will images modification get me a better machine learning model? I have the following scenario. Camera is fixed and does photos of a process. The process has a few states. Now I want to train a model ...
0
votes
2answers
121 views
0
votes
0answers
10 views

Data set compatability with LSTM's or convLSTM's

I am currently working on a data set which has the structure - frames x Number of Objects. Each object is of size 7x5 and the task is to classify each object into one of the 4 classes. I have been ...

1
2 3 4 5
11