# Questions tagged [classification]

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.

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### How can one classify data if the range of possible features is continuous/infinite?

Imagine my instrument encodes colors using any/all possible wavelengths of light (not just the 3 features red, green, blue). Thus, it has an “infinite” number of features lying on a continuous ...
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226 views

### random forest classification appears dependent on Dependent variable proportions

I'm using Random Forest for classification which gives the following confusion matrix. 0 1 class.error 0 839 24 0.027 1 60 86 0.410 You can notice that the ...
1answer
212 views

### Classification with partially labelled data - potential positives

I am having trouble figuring out the best approach for a classification problem: My data: For each physician in my data, I have a feature set of every different medical procedure where the feature ...
1answer
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### Classifying 3 groups statistically on a continuous scale

I have 3 subsets, say- a,b,c which are derived from a single population of subjects. All subsets have an unequal "n", and are accompanied by a variable say 'L'. My aim is to define a metric (based on ...
1answer
196 views

### Classification: training sets different sizes

I'm building a classifier for text analysis sentiment. I have a large training set for positive, neutral and negative mentions. Should the training data sets be similar in size? Currently my ...
1answer
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### Classification method with (potentially) endless training input

What is the best multi class classification method with (potentially) endless training input? The classificator should get trained while a user interacts with the system. At this time it gets ~ 30 ...
1answer
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### How to embed prior distribution of datasets into the classification model

Given 3 training sets : $(X_1,y_1),(X_2,y_2)$ and $(X_3,y_3)$. These three datasets are separated as it is being manually tagged in the preprocessing. Based on the datasets, three classifiers can be ...
1answer
61 views

### Predicting continuous position using input variables of unknown quality

The problem I'd like to solve can be reformulated as follows. Let's consider that I have to go to some parties and I would like to find out where in the room I am most likely to have a good time. I ...
1answer
105 views

### How do I learn a simple cut-off value between 2 classes given one-dimensional data?

Given a set of data which consists of a single real number and a class, I want to find a value (i.e., the inflection point if we were talking about logistic regression) which would lie right at the ...
1answer
159 views

### Conceptual diffiulty in understanding multiclass classification

Given a high dimensional feature vector x in $R^D$, I want to map it to an L bit vector, $L << D$, z = h(x) in $\{0,1\}^L$ using a function h while preserving the neighbors of x in the binary ...
1answer
24 views

### Classification when variables are observed as a group

How do I classify variables when the classifying binary output is known only for groups of variables? Here is a concrete example: a person eats different types of foods on different days, and she ...
0answers
207 views

### Does Gaussian discriminant analysis and linear discriminant analysis refer the same algorithm?

I'm pretty new to LDA and I came across other terminology called Gaussian discriminant analysis elsewhere. Since LDA assumes the normality or normal distribution of the data which is same as ...
0answers
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### Classification of real values

I have values of attribute between 0 and 1 which i want to predict. The distribution of values is shown in fig. I want to predict this attribute. The problem is there are around 15 classes in this ...
1answer
771 views

### How to represent no-detection in a confusion matrix

So let's say we have a multi-class classification problem and we want to represent the outcomes as confusion matrix. All the examples I'm finding on the web asume that all the elements are detected. I ...
0answers
59 views

### Suitable non-deep classification algorithm for binary images

I've to classify images of hand shapes like this: I've tried this methodes actually: SVM with contour vector of the hands shape as features PCA on images pixels + SVM Have you other ideas to deal ...
1answer
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### Can cluster analysis of preclassified items gives idea about the classification performance?

Suppose in a classification we have a dataset with many features and their class, we want to select some features using which we can construct a classifier. We perform the cluster evaluation for the ...
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### Models that can learn incrementally

I want to implement a multinomial text classifier for my 3 classes 'A', 'B' and 'C'. This classifier should be open, in the sense that it should be extensible with new data. Using the hashing trick it ...
0answers
157 views

### What are the reasons why a classifier could produce bad results?

I know of four possible reasons: overfitting underfitting input data doesn't represent the problem (which I guess is underfitting) classifier isn't suitable (e.g. problem is not linear) Are there ...
0answers
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### Grouping labelled object, not unsupervised clustering: Any method? Hidden markov models?

Say I have many articles, with the following labels. "classical music","pop music","physics","chemistry". Then an obvious way to group these labelled data is to group the former two under the "music" ...
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### Interpretation of results regarding ROC plot on training a classifier with caret and randomForests R packages

@Dear People, i used firstly the function train() from caret package, to construct-train a classifier with random forests on a merged microarray dataset regarding selected genes, for a binary outcome(...
0answers
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### What are the best practices and methods to classify a time-dependent variable?

Imagine we are collecting some feature values (like temperature, pressure etc.) every now and then and we also record the status of an equipment (which could be healthy or faulty); like below. Status ...
0answers
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### How do I estimate the acceptable range?

I need to classify candidates as "good" or "bad" where a "good" candidate's age and income, say, must fall within some ranges; I'm trying to discover the boundaries for those ranges. A candidate must ...
1answer
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### Finding object in the image

I'm working on building a classifier that needs to find one particular object in the photo. I'm planning on using SIFT/SURF + kmeans for feature extraction and logistic regression for classification. ...
0answers
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### I have two classes and several characteristics. Is there a way to build a profile of the typical observation of one class?

I have thousands of observations and 20+ characteristics (way more if you transform them from categorical to binary characteristics). Is there some method that can be used to build a profile of the ...
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84 views

### Name for a data preparation technique for classification

Say I am looking to classify an object based on certain patterns of events that occur. If I want to use classification, one easy way to do it is to divide the time up into some unit (like per day), ...
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81 views

### What are the problems of these decision trees outputs?

I have a report that using two structures of decision trees for a multi-class (4-classes) classification problem with 7 inputs. First output is for ...