Timeline for Classifiers and accuracy
Current License: CC BY-SA 4.0
9 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Aug 14, 2020 at 16:31 | vote | accept | Math | ||
| Aug 14, 2020 at 16:28 | comment | added | Math | Let us continue this discussion in chat. | |
| Aug 14, 2020 at 16:10 | comment | added | Ashwin Geet D'Sa | Yes, you are missing something. If you want to classify based on the number of words (it can be simply considered as an algorithm).Building a vocab, etc are all part of prepocessing. | |
| Aug 14, 2020 at 15:53 | comment | added | Math | So the main part would be preparing the data; then, the model chosen would do the rest, would it not? I have this doubt as when I think of email classification I have some words which can allow me to distinguish between spam/not spam. Of course, if I have a labelled dataset, I should get a vocabulary made by all words from spam set and another one made by words from not spam set. Then, based on their frequency in each email in the test set, I should be able to classify them. Am I missing something? | |
| Aug 14, 2020 at 15:47 | comment | added | Ashwin Geet D'Sa | If you starting with your own data, then you may have to label the data that you collect. | |
| Aug 14, 2020 at 15:47 | comment | added | Ashwin Geet D'Sa | Usually, if you go with standard datasets, they are already labelled. Cleaning/Preparing the data is required, but it is also dependent on the algorithm or the features for algorithm that you would like to use. | |
| Aug 14, 2020 at 15:36 | comment | added | Math | My doubt was the following: when I read about how people determine spam/not spam, fake l/not fake news, all of them mention only algorithms (SVM, Naïve Bayes,..) without specifying anything. Then they mention the accuracy of test. So what I would like to understand is if the only thing which is important is to clean/prepare data and adding manually labels first as data usually are got without labels. | |
| Aug 14, 2020 at 15:29 | comment | added | Math | Thank you so much Ashwin. So after preparing the dataset, cleaning it and split it, the only thing to do is just to apply algorithms. I do not need to built a new algorithm from scratch? | |
| Aug 14, 2020 at 15:10 | history | answered | Ashwin Geet D'Sa | CC BY-SA 4.0 |