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Results tagged with classification
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user 4598
Statistical classification is the problem of identifying the sub-population to which new observations belong, where the identity of the sub-population is unknown, on the basis of a training set of data containing observations whose sub-population is known. Therefore these classifications will show a variable behavior which can be studied by statistics.
2
votes
Evaluating the quality of a classifier which provides probability per class
If your objects do belong 100% to one class each, then you can
set a cutoff and calculate "hard" memberships from that => gives normal sensitivity & Co. (for explanation of their meaning, see e.g. …
- 39.6k
1
vote
70% certain with a 70% success rate
You're looking for the precision. In the context of medical diagnosis, it is called the positive predictive value.
As @image_doctor already commented, knowing the prior probabilities of your classes …
- 39.6k
36
votes
Accepted
How large a training set is needed?
classification method
complexity of the classifier
how well the classes are separated. … DOI: 10.1016/j.aca.2012.11.007
accepted manuscript on arXiv: 1211.1323
This is the "teaser", showing an easy classification problem (we actually have one easy distinction like this in our classification …
- 39.6k
1
vote
Cross validation for classifiers
Cross validation or more precisely: resampling validation relies on some assumptions. Relevant for your question are:
A (surrogate) model trained on the whole data set minus a few cases (the left-ou …
- 39.6k
2
votes
Confidence Interval - Binary classification
I'm not sure for which property you need the confidence interval, but here we go:
In case you need confidence intervals for the validation results (i.e. classifier has accuracy of p ± Δp), for propo …
- 39.6k
1
vote
AUC / FPR / TPR , confused with testing vs training set
You need to decide two fundamentally different things when measuring the performance of a predictive model:
A plan how to get appropriate test cases, and
figures of merit that measure the performance …
- 39.6k
1
vote
Classification when there is dependance between some classes but not others
Have a look into one-class classification. … In medical diagostics, discriminative classification (the "usual" classifiers) would typically be appropriate for differential diagnostics. …
- 39.6k
1
vote
Accepted
High variance across k-fold CV classification accuracy estimates
A few thoughts:
for a (true) accuracy of $p = 63\,\%$, a standard deviation of the observed accuracy $s_{\hat p}$ of 3 % would be expected for testing with roughly 250 cases (using binomial distribu …
- 39.6k
2
votes
Checking whether accuracy improvement is significant
Applying Erik's answer to Michael's:
You can do the same kind of thinking Erik refers to when choosing the performance measure.
I find it helpful to refer to different such measures by the questi …
- 39.6k
2
votes
What is crisp logic (in the area of classification)?
crisp / fuzzy is used in fuzzy logic
hard / soft is sometimes used for continuous classifier scores in [0, 1] as well, e.g. in the remote sensing community.
Interpretation of continuous [0, 1] sco …
- 39.6k
2
votes
Accepted
Combine Clustering and classification
However, I'd still call it rather a (predictive) clustering model than a classification.
There are one or two points you need to keep in mind. …
- 39.6k
14
votes
Accepted
Is cross-validation still valid when the sample size is small?
.: Sample size planning for classification models., Anal Chim Acta, 760, 25-33 (2013). …
- 39.6k
11
votes
Should PCA be performed before I do classification?
"PCA chooses the directions in which the variables have the most spread, not the dimensions that have the most relative distances between clustered subclasses."
LDA projects the data so that betw …
- 39.6k
10
votes
Accepted
Good classifiers for small training sets
First of all, you may want to have a look at the Elements of Statistical Learning. They discuss variable selection as well as different regularization techniques in chapter 3 (never mind it being abou …
- 39.6k
9
votes
Why do researchers use 10-fold cross validation instead of testing on a validation set?
In my field (classification of biological/medical samples), sometimes a test set is kept separate, but often it comprises only few cases. …
- 39.6k