Questions tagged [labeled-datasets]

The tag has no usage guidance.

Filter by
Sorted by
Tagged with
2
votes
1answer
52 views

What problem does the neural network really solve?

In the image below taken from a Youtube video, the author explains that the neural network can be used to fit a relational graph for a set of data points shown by the green line. And that this is ...
0
votes
1answer
59 views

How do I prepare my data for a CNN to be applied to a geophysical-related problem?

I am currently doing research work on an inversion of geophysical data using Machine Learning. I have come across some research work where a Convolutional Neural Network (CNN) has been used ...
7
votes
1answer
158 views

How to deal with a small amount of labeled samples?

I'm trying to develop skills to deal with very small amounts of labeled samples (250 labeled/20000 total, 200 features) by practicing on Kaggle "Don't Overfit" dataset (Traget_Practice have ...
2
votes
1answer
41 views

Is intersection of labels acceptable in computer vision?

I have a dataset, where objects are very close to each other. So, the question is: what is the best approach to label them? There are two possible options: mark objects so that they will not ...
4
votes
3answers
97 views

If the accuracy of my current model is low ($50 \%$) and we want to minimize time in collecting more data, should we try other models?

Suppose we have a data set with $4,000$ labeled examples. The outcome variable is trinary (three possible categorical values). Suppose the accuracy of a given model is "bad" (e.g. less than $...
5
votes
2answers
648 views

What is the effect of mislabeled training data?

Collecting and labeling training data for supervised learning tasks is incredibly time-consuming and costly. For instance, let's say you wrote a script that went on Google images and got you 5000 ...