# Questions tagged [model-selection]

Model selection is the process of comparing several models and their respective results to choose the model is best according to some evaluation metric.

215 questions
Filter by
Sorted by
Tagged with
1answer
23 views

### Remove frame from background

I am having 400 images that look like the following: I would like to remove the frame and only get the image in the middle: I tried the MODNet model ...
0answers
6 views

### How to properly measure forecast errors when predicting correlation coefficient?

My task is to accurately predict correlation coefficient value. I have some candidate models, and want to select the best one (with minimal forecast errors on validation dataset). I don't feel good ...
0answers
23 views

### What model to train to restore MNIST test dataset

I came across this problem, and not sure where to start. What model would work best for this problem and why? Imagine the digits in the test set of the MNIST dataset (http://yann.lecun.com/exdb/mnist/)...
0answers
22 views

### How to go about predicting administrative fees?

We collect administrative fees from our customers based on many complex business rules albeit based on few variables. I have the history of fees colected through time (about 500 records for each ...
1answer
178 views

### How can I choose the best machine learning algorithms from all kinds of algorithms?

When I want to find a model for my data set, I find that there are lots of algorithms that I can use. I know how to minimize selection choices by separating supervised and unsupervised algorithms and ...
1answer
20 views

### how to choose the best machine learning algorithms from all kinds of algorithms? [duplicate]

guys, I am a beginner at data science and I’ve been learning machine learning for a while with some courses online without any help of a teacher and after I’ve got to work with some real projects on ...
0answers
30 views

### Is it possible to derive anything useful from this piece of data?

Let's say you have online Profile A. Profile A is present on 3 websites: X, Y, Z. ...
1answer
21 views

### Which regression models should be used with very tiny dataset?

I have a very tiny dataset to make a regression model. only 22 data points with just 2 float features and 1 float output. I want to make models among sklearn ...
0answers
14 views

### EDA and Attribute selection [closed]

I have a dataset regarding traffic-violations. The attributes are as follows: ...
1answer
77 views

### What are the most known ML-models that use complex numbers? (if there are any)

Basically just the header. The question is out of curiosity as I haven't seen one yet.
1answer
11 views

### How can I learn to better explain architectural choices?

I've found out that most of the choices made during model selection are based on a sort of trial and error. From what I've heard, even the most experienced Data Scientists cannot know beforehand ...
0answers
36 views

### Silhouette Score for different Clustering algorithms

I am trying to compare different clustering algorithms on a dataset and compare the model performance. Since the dataset is quite big (56 features), I applied PCA to reduce the number of features to ...
0answers
20 views

1answer
42 views

### Learning Curves and interpretations

I've trained 4 classifiers on an undersampled dataset. I plotted the learning curve for each classifier and I got the following results : I see that for the Log Reg, both curves seem to converge and ...
1answer
72 views

### Does RandomForest convergence imply I can solve a problem with a NN too?

I'm trying to perform a regression on a dataset, and I've been testing a few models, mostly for practice. I was able to get good results with a RandomForestRegression model, as you can see in the ...
1answer
45 views

### Machine Learning Method For Creating Chemical Formula

We work at chemical company . We have nearly 3000 chemical formulas which is composed with chemical raw materials. Our chemical formulas is composed of 20-25 raw materials. As you guess, amount of ...
1answer
134 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 - ...
1answer
46 views

### Model Selection using Bias Variance Trade Off

I have a Regression Model with Train MAPE as 6% and Test MAPE as 15%. This appears to me as a clear case of over fitting. But can I still use this model assuming 15% Error is not a bad number after-...
1answer
23 views

### Is there a quantitative way to determine if a class of algorithms tends produce low bias or low variance models?

I understand that some machine learning models tend to be low bias, whereas others tend to be low variance (source). As an example, a linear regression will tend to have low variance error and high ...
2answers
64 views

### How do you, analytically, show you are not using too many features?

One of the managers at my company asked if there is a I could include a metric demonstrates that the my model is not using too many Features/Variables. Is there a metric or best practice that does ...
0answers
25 views

### How to balance time/effort with transformations, feature selection, and models efficacy in nlp? [closed]

Edit: Question has been edited for reopening (see comment section for justification) Being to new text analytics, I haven't gotten the hang of navigating a typical workflow given the longer times ...
1answer
162 views

### Why does a simpler model performs better than a complicated one?

This has happened to me, a complicated model couldn't solve the problem when a simpler one solved it in a few epochs. How is that? I believed that a more complicated model means more number of ...
1answer
24 views

### Model selection in active learning

I am dabbling in active learning and was wondering how to combine this in seeking out the best architecture for the network. In my understanding, active learning uses a heuristic for selecting the ...
0answers
24 views

### Comparing different machine learning methods over multiple test datasets with different number of samples [closed]

Say, I have an image dataset (for example, imagenet) and I am training two image recognition models on it. I train a resnet with 10 layers 3 times on it (each time with different random weight ...
1answer
179 views

### model selection in clustering

I am working on a mall customer segmentation dataset (5 features, 200 rows) using clustering. This dataset does not have any ground truth labels. I had a few doubts regarding clustering: Can I use ...
3answers
463 views

### Is autocorrelation of residuals a problem in machine learning?

Let's assume I have a random forest model and the residuals of the model are autocorrelated. Is this a problem? As an example, let's assume I have two different random forest models, A and B, with a ...