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
2
votes
1answer
9 views

Phrase/Token labeling

Looking for suggestions on how to define the following NLP problem and different ways in which it can be modeled to leverage machine learning. I believe there are multiple ways to model this problem. ...
0
votes
0answers
9 views

Keras model's embedding weight get NaN value

I am working on 3 categorical and 19 numerical features in which I plan to use trained embedding weights (from categorical features). After training, and get weights from embedding layers, I got NaN ...
1
vote
0answers
7 views

Building crop recommender system with past cultivation data not with ratings

I am planning to create a Crop recommendation system for farmers using the past ten years' crop cultivation data. it is a mobile application. whenever a farmer selects his location, the system will ...
0
votes
0answers
15 views

Dense Keras network returns constant output, even for very simple models

I am trying to use keras dense neural networks to forecast some time series. When fitting my model on complex real datasets, my model converges toward a constant output, i.e. whatever the input, the ...
0
votes
0answers
9 views

how to determine the relationship between attributes/whether one has impact the other

I am trying to build a model that determines whether two products have an impact on each other's sales performance. Ideally, the result will provide me a ranking/score between each 2 product pairs. I ...
0
votes
0answers
17 views

How to estimate Coal Level in a Coal Train

I want to estimate coal level in each of the bogies in a moving coal Train. I want to get the percentage of how much it is filled. Can anyone please suggest me how should I proceed?
0
votes
0answers
12 views

pytorch lightning produces no checkpoint when learning rate fine tuning ison

My problem is concerning with using the automatic learning rate finder of pytorch lightning. In case I use this feature there isn't any checkpoint output produced at any time during the training of ...
1
vote
1answer
35 views

How to set the priority to Machine leaning algorithms for Binary classification among Four based on accuracy and fitting

Rain Classification in Australia Under this context, sklearn classification algorithms will be used, namely: Logistic Regression Classification (Parametric) Decision Tree Classification (Non ...
0
votes
1answer
37 views

Why is my Neural Network having constant loss and always predicting a singular value?

I am trying to make a neural network on a dataset with 257 features and 1 target variable. My code looks like the following: ...
0
votes
0answers
17 views

Features importance in model

I've been using azure's auto ML platform for a couple of weeks now and recently I've trained a model and came across a strange looking aggregate feature importance chart in the explanations tab. The ...
0
votes
0answers
12 views

How to perform nonlinear regression on data with error?

Most of of physical measurements are associated with error, I am wondering how to perform nonlinear regression in this situation. In the linear case, there are few methods like Deming Regression, ...
1
vote
1answer
23 views

Low P value in Chi-squared test but low coefficient in logistic regression

I ran a chi squared test on multiple features & also used these features to build a binary classifier using logistic regression. The feature which had the least p value (~0.1) had a low ...
0
votes
0answers
13 views

Categorical variables: create a risk class or include in the model?

I think this is a very basic question so sorry for the wordy format. I am trying to get my head around it. I am thinking about predicting earthquake damage to property in the US using a GLM algorithm. ...
0
votes
1answer
15 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 ...
0
votes
0answers
20 views

Should Chi Squared test for feature selection be applied on train dataset or the whole dataset?

I am working on building a logistic regression model. I am planning to run chi squared test for feature selection. Should I run it on train dataset or the whole dataset?
1
vote
1answer
26 views

In Text Classification if I get similar performance with 100 features and 200 features, which model should I go ahead with?

I have built two text classifier models, one has 200 features the other has 100 features (reduced to 100 from 200 after feature selection). I see similar performances in both. Which model should I go ...
1
vote
1answer
14 views

Shouldn't a test be repeated X times and average the results to determine the best machine learning model?

I have searched in several web pages how to choose the best machine learning model for a dataset and they all seem to agree that they should be compared using the same seed. However, they only run the ...
0
votes
0answers
18 views

Can there be scenarios where an overfitted model in machine learning cannot be generalized?

Is it always possible to generalize an overfitted model? I know there are ways to handle overfitting, but can there be scenarios where overfitting cannot be handled in machine learning?
1
vote
0answers
13 views

Rule of Thumb for number of observations required to train a model with n independent variables?

I am aware adding more features to a model leads to overfitting of a model. Is there a rule of thumb for minimum number of rows required to build a model with n features in order to build a ...
0
votes
1answer
20 views

How to use new dataset on a pretrained neural network model?

I have built a dataset that I would like to pass to a pretrained model in oder to perform some predictions. I am looking for some steps/processes to guide me in this. Should I fine tune?If so what ...
0
votes
0answers
8 views

Weight for Samples on SVM

there is a option sample_weight in fit(X[, y, sample_weight]) function (OneClassSVM, sklearn library). If I use the option ...
1
vote
1answer
32 views

How can I weight each point in one-class SVM?

I want to give weights to some data points Specifically, these are points related to anomalies (I'm implementing one-class SVM for anomaly detection) Exactly, I want to consider some data points that ...
1
vote
1answer
11 views

Measure performance of classification model for training on different snapshots

I am trying to do binary classification on some chronological data. Let's assume we have weekly data from the first week of 2017 through the last week of 2020. Now we have found out that 26 weeks of ...
0
votes
0answers
94 views

Why am I getting a different answer in Principal Component Analysis dimensional reduction?

Problem-: Consider the two dimensional patterns (2, 1), (3, 5), (4, 3), (5, 6), (6, 7), (7, 8). Compute the principal component using PCA Algorithm. Use PCA Algorithm to transform the pattern (2, 1) ...
0
votes
1answer
51 views

Can someone explain the solution to the following problem?

Q) We want to learn a function f(x) of the form f(x) = ax + b which is parameterized by (a, b). Using squared error as the loss function, which of the following parameters would you use to model this ...
0
votes
0answers
31 views

Regression trees for extrapolating time series data

This is a regression problem that involves predicting the price of e.g. aluminum, oil, strawberries. I have hourly and half hourly data for the weather and up to 10 different socioeconomic variables (...
0
votes
0answers
44 views

Com posso resolver esse erro: TypeError: a bytes-like object is required, not '_io.BufferedReader'

msg: erro: TypeError: a bytes-like object is required, not '_io.BufferedReader' My code: import pickle with open(b'ModelosParaTrader/ModeloEurUsd.pkcls', 'rb') as modelo: lr = pickle.loads(modelo) lr
0
votes
0answers
6 views

How to import SAS model ZIP file into python?

Is there a way to load a trained SAS model exported from Viya in ZIP file format into Python? I mean, kinda like loading a trained model from a pickle file. If it helps, here's the content of the ZIP ...
-1
votes
1answer
43 views

nested cross validation vs. train-test split

I am trying to understand the main benefits of conducting a nested cross-validation compared to a simpler train-test split. Let us say I would like to build a prediction model. I initially split my ...
0
votes
1answer
38 views

How to introduce bias in a machine learning model?

How can I introduce bias for a decision tree model while building an ML application? e.g. If I am building a stock trading recommendation algorithim, I would want to recommend a stock only when the ...
2
votes
0answers
41 views

Understanding the math behind linear classification [closed]

For example we have $X$ train data, $y$ and $w$ Our margin is $M = y_i \langle w, x_i \rangle$ If $M_i > 0$ classifier return True predict and otherwise, if $M_i < 0$ we get False predict. How ...
1
vote
5answers
205 views

What is the best way to train a model?

I am trying to train my model for sports predictions. The data frame is as a below given example: ...
0
votes
0answers
20 views

Does linear classifier creates linear decision boundary in the input feature space?

I read a lot , but still not able to get the following concepts -: (1) If a classifier is given, how do we know whether its a linear or non linear classifier? (Interested in step by step procedure to ...
0
votes
0answers
13 views

Image classification - first production coding try

TLDR Experienced non-ML developer has done the basics to learn beginner ML, now needs to put it to real use - looking for help. ...I guess a common/frequent situation for many! For mods - I've tried ...
0
votes
1answer
11 views

Gradient descent different implementation cause error

We know that we can get closer to the local minimum of the function by descending our argument according to that rule $$w1 = w0 − γ∇f$$ For example I have a linear regression model that depends on $b,...
1
vote
0answers
18 views

Which algorithm to use for a very simple ranking problem?

Currently, I have a dataset with 10 features that results in a ranking of 4 items, i.e. [1,2,3,4], [4,3,1,2], [3,2,4,1] or any $4!$ permutations that can arise from the ranking. What algorithms are ...
2
votes
0answers
24 views

Cross correlation

I am trying to find a good algo (low latency) that is able to take two time series and determine which one is leading on the other one if any. The time series do not necessarily have the same ...
1
vote
0answers
28 views

How can I prepare my discrete batches of data for training?

I'm trying to calculate effect of parameters of an operation on the thickness of a wall. Each operation is thinning the wall thickness and at some point the wall is replaced and operation starts again....
0
votes
1answer
24 views

Use of multiple models vs training a single model for multiple outputs

So let's say I have data with numerical variables A, B and C. I believe that the value of a has an effect on B. I also believe that A and B both have an effect on C. I don't think C has an effect on ...
0
votes
0answers
17 views

What type of clustering algorithm to use to determine what accounts belong to a family?

I have both categorical (Name, address, etc.) and numerical data (similarity scores between two parameters) and I can't figure out what kind of clustering ML algorithm would be appropriate since most ...
0
votes
1answer
28 views

Division of data into training and validation sets

I have a multi-sensory dateset for the activities of daily living. It contains data from 10 volunteers each performing 9 activities. Each volunteer wears 6 sensors on their body with the recorded data ...
0
votes
1answer
23 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 ...
2
votes
1answer
51 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 ...
0
votes
0answers
28 views

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 ...
0
votes
0answers
11 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. ...
0
votes
1answer
24 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 ...
0
votes
1answer
47 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 (...
0
votes
0answers
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 ...
0
votes
0answers
58 views

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: ...
1
vote
0answers
28 views

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 ...

1
2 3 4 5
12