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 ...

learn more… | top users | synonyms

0
votes
0answers
6 views

F1 score for biased binomial data

I am applying a Bayesian classifier and would like to find out the f1 score. I determined the TP, TN, FP, TP. Unfortunately I had to find out that in my cross-validation almost in all test scenarios ...
1
vote
0answers
23 views

Linear regression of 0/1 response (Fig. 2.1 of The elements of statistical learning)

In chapter 2 ESL book authors write: Let's look at example of linear model in a classification context They fit a simple linear model $g = 0.3290614 -0.0226360\cdot x_1 + 0.2495983 \cdot x_2 + e$, ...
0
votes
0answers
12 views

The ethics of using an optimal multiclass feature set for binary classification

I'm currently trying to find the best feature set/network architecture configuration for a binary classification problem, however to approach it via the usual means of building and testing does not ...
1
vote
2answers
30 views

Cost functions for weighting sensitivity and specificity in binary classification problem

I'm searching for a combination of sensitivity and specificity cost function because i want have more weight for sensitivity ( ...
0
votes
0answers
7 views

Feature selection based on cost function

Suppose that we are searching for best features using an optimization algorithm for a classification model (MLP,SNM,Regression,etc...). We should set a cost ...
1
vote
1answer
25 views

Classification tips for a begginer

I'm doing a graduation work that involves applying Classification algorithms in a dataset of matches from Dota 2 (a popular MOBA game). Here's an explanation of the problem: Dota 2 matches are played ...
0
votes
0answers
15 views

Logistic Regression with different priors

I am using standard logistic regression for classification with reasonable results. As expected I get a probability of 0.5 for query points "far away" from the data. However I would like to assign ...
0
votes
0answers
14 views

Having additional data for only a subset [on hold]

Due to having a maximum amount of data i can request, I can only request additional data for only a targeted group that I am interested in. This data should help my model accuracy for the targeted ...
1
vote
0answers
22 views

Optimize number of layers and neurons with an optimization algorithm

I have a neural network that i want optimize number of hidden layers and neurons in every layer using an optimization algorithm like ...
0
votes
1answer
20 views

Composition of bankruptcy probability and firm size

I'm using neural network for a binary classification problem of bankruptcy prediction using patternnet function in MATLAB, so i ...
1
vote
1answer
29 views

What is a good AUC for a precision-recall curve?

Because I have a very imbalanced dataset (9% positive outcomes), I decided a precision-recall curve was more appropriate than an ROC curve. I obtained the analogous summary measure of area under the ...
0
votes
0answers
10 views

Multi-class logarithmic loss function per class

In a multi-classification problem, we define the logarithmic loss function $F$ in terms of the logarithmic loss function per label $F_i$ as: $$ F = -\frac{1}{N}\sum_{i}^{N}\sum_{j}^{M}y_{ij} \cdot ...
0
votes
0answers
16 views

Stream classification of time series

I have a set of time series $\mathcal{Y}$, and a test time series $T$ for which I need to find the closest matching time series $Y_i \in \mathcal{Y}$. This has to be done online, i.e., $T$ is a stream ...
1
vote
1answer
40 views

Does Fisher linear discriminant analysis (LDA) require normal distribution of the data in each class?

Does Fisher linear discriminant analysis really require the data distribution in each category to be normal? I see two versions. The first one states that it requires the normal distribution and ...
0
votes
0answers
2 views

How can I counteract the effect of a degenerate classifier in an OVA Model?

Suppose I build a OVA classification model for classification with more than 2 possible classes (a model of sub-models, where each submodel predicts the probability of a data point belonging in a ...
1
vote
0answers
6 views

permutation test with a distribution of correct values

I want to test my classifier performance using a permutation test. I know how to test one actual value against a null distribution of values generated by randomly reassigning labels to my two classes. ...
0
votes
0answers
42 views

The best way to solve particular classification problem?

I got training set (time series) of size approximately 2 million precedents {x,y}. Each x is a vector of size 20 and each y is a binary vector of size 10 like {1,0,0,1,1,0,1,1,1,0}. For a new input x ...
1
vote
0answers
26 views

Order of preprocessing steps in a binary classification problem

I have these stages (ordered) for preprocessing in my binary classification problem. Dividing data based on criteria (class1 and class2 databases) Outlier ...
0
votes
1answer
29 views

Best algorithms for ordinal classification

I am working on a data set of about 34K rows trying to predict an ordinal response variable using R. I have tried association rules, random forest and ordinal regression. Does anyone have experience ...
0
votes
0answers
35 views

Cutoff and precision values of a binary classifier

Let's say I have fitted a binary classifier to some data and I'm varying the cutoff value, effectively producing a ROC-curve. Knowing the true proportions of positives and negatives, I can calculate ...
0
votes
1answer
53 views

Classification using correlation

Given two correlation matrix (each $p \times p$), where each belongs to a different group, is it possible to classify a new sample into one of the group (based on the correlation matrix only)? What ...
1
vote
1answer
61 views

How to change threshold for classification in R randomForests?

All the Species Distribution Modelling literature suggests that when predicting the presence/absence of a species using a model that outputs probabilities (e.g., RandomForests), choice of the ...
0
votes
0answers
26 views

different feature types for classification

There has a data set with several features. One feature is of the type of continuous numerical values; another feature is of the type of categorical values, such as A, B and C. If I want to build a ...
0
votes
0answers
7 views

Clustering techniques when there are two distinct but numerically similar clusters among others

I'm trying to cluster some spatial statistics for some behavioral estimation. However, parts of the trajectory report exactly 0 speed, which implies some kind of resting state which is different from ...
0
votes
1answer
21 views

R regression with categorical response variable

I have four variables, two are categorical and two are numeric: ...
0
votes
2answers
155 views

When to avoid Random Forest?

Random forests are well known to perform fairly well on a variety of tasks and have been referred to as the leatherman of learning methods. Are there any types of problems or specific conditions in ...
0
votes
1answer
15 views

Use random forest outliers to detect group of variables

I have a input data and an output binary variable . The y value is 1 if the patient get ill. ...
1
vote
0answers
16 views

Comparing 2 classifiers with different feature vectors based on same training and test data

Let us assume we have two classifiers C1 and C2 which are based on different feature vectors, ...
0
votes
0answers
10 views

Completing a matrix whose entries depend on time

Imagine you have a matrix, where each row represents an individual and each column represents a specific time interval. The entries of the matrix represent events occurring for a given person at a ...
2
votes
0answers
72 views

How many eligible bachelors in a city?

This is a very simple question posed to me by a friend of mine. I know it's a statistical analysis problem, but I suck at math. Given the total population of $x$ within a metropolitan area, what ...
0
votes
0answers
8 views

automatic assign class name based on text

My question is , I have a set of plain text , i want to create category based on the text. Eg: i have written something about Soup recepie then the algorithm must create a category called Food. After ...
1
vote
1answer
64 views

Outlier detection in out-sample data for the purpose of classification

This is the most widely used method for outlier detection in econometrics and statistical problems. X is our data that we're searching for outliers in it (in ...
1
vote
0answers
30 views

categorical feature ranking

I would like to rank categorical features by the order or importance in a classification/regression setting. Input There are two features, which are survey questions: "how is your mood?": four ...
1
vote
1answer
20 views

How should the precision/recall be calculated for classes in datasets with NO true class instances?

I have built a classification model to recognise a class and I have evaluated it on several datasets. The problem is that some of these datasets do not have any true instance of the class in question, ...
0
votes
0answers
3 views

what is the meaning of the Samples in NER?

I would like to know in NER (Named Entity Recognition ) problem , which concept should be considered as samples? each token as a sample? or each sentence ? or each Named Entity should be considered ...
0
votes
0answers
34 views

Selecting individuals from a population using a binary classifier

I have a dataset consisting of around 200 individuals, whose outcome is either of state $0$ or $1$. I am able to make binary classifiers and predictors on this set and build ROC-curves for them just ...
1
vote
0answers
37 views

Adaptive Boosting vs. SVM

I am working on a binary classification case and comparing the performance of different classifiers.Testing the performance of adaboost algorithm (with decision ...
0
votes
0answers
13 views

Implementation of batch Hieron

I would like to implement the Hieron algorithm, which is described in the paper "Large Margin Hierarchical Classification". The basic online Hieron is specified in the paper, but I need the batch ...
1
vote
3answers
119 views

ROC graph shape

Could you explain to me how the shape of a ROC curve is determined? From the following illustration, it seems that for every time the actual class (C) is positive, it goes up and when it's negative, ...
2
votes
0answers
44 views

Unbalanced dataset - ROC curve to compare classifiers?

I use the machine learning software WEKA for data mining on biological data. I would describe my dataset as unbalanced: It comprises around 2000 instances, ...
2
votes
2answers
92 views

Reproduce linear discriminant analysis projection plot

I'm struggling with projection points in linear discriminant analysis (LDA). Many books on multivariate statistical methods illustrate the idea of the LDA with the figure below. The problem ...
0
votes
2answers
37 views

Evaluating predictive models

I am looking for ways of evaluating the performance/success of predictive (classification) models for economic purposes. I know of: Direct accuracy percentage AUC score Net profit Rate of return ...
0
votes
0answers
8 views

Inconsistency in labelling a class for a churn prediction problem

I'm modelling a classifier to predict churns. I have a set of training instances which are a tuple of the form (attributes, label) where the label says whether they are active (call the label as "A") ...
0
votes
0answers
8 views

How can the quality of features be evaluated in high dimensional classification tasks?

I am currently experimenting with on-line symbol recognition for mathematics for my bachelors thesis. I have 369 symbols which I would like to distinguish. There are a lot of preprocessing methods / ...
1
vote
0answers
22 views

Document classification problem

Assume we have $L$ labelled documents, and $U$ unlabeled ones, where all the documents from class $k$ were generated from a multinomial or Naive Bayes distribution with parameter $\theta_k$, and ...
0
votes
0answers
32 views

Parameter optimization of SVM

Currently I am using SVM to perform some classification task. I use libSVM with Matlab interface. From the practical guide of SVM (Link), we know that there are two parameters need to be tuned, namely ...
2
votes
0answers
10 views

In binary classification, what label imbalance is acceptable to not to care?

I have a pretty large set of binary-labeled data (~20K rows, ~100 columns). Approximately 20% of the data is "positive" and 80% is "negative". In my case every classification error has the same ...
0
votes
0answers
9 views

Weka: cross validation using blocks of related instances (leave one patient out)

I have a dataset that comprises several instances for different patients, with multiple instances per patient. I need to perform some classification tasks and I was using cross-validation, but this ...
1
vote
0answers
16 views

Learned production test

To validate the acoustic performance of a product, we are using hand-engineered features and thresholds. Everytime a new hardware problem arises we have to at least tweak a parameter and at worst add ...
3
votes
0answers
36 views

Priors for discriminative methods?

Say we want to build a classifier for a binary classification problem using a discriminative method (e.g. SVM) and be able to impose a prior on the classes. For example, let's assume that we want to ...