Questions tagged [labeled-datasets]
6 questions
10
votes
1 answer
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 provided all 20,000 Targets). I've read a ton of papers and…
FirePower
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5
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2 answers
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 pictures for each of 10 classes. You then use an…
pshlady
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4
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3 answers
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 $50 \%$).
Question. Should you try different traditional…
naturalguy_12
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2
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1 answer
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 accomplished by using weights, biases and activation…
LinusMagnola
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2
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1 answer
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 intersect (it is difficult, surroundings are not included…
Valery Noname
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0
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1 answer
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 effectively for this purpose (for example, his).
I am…
W. Oni
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