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
1answer
11 views

how a cosine similarity measure can be made a distance measure

I want to make cosine similarity a distance measure for undersampling of fraud data , but the problem is if I get the zero values it will give 0/0, what can I do for this what can be the ...
2
votes
0answers
15 views

Calculating ROC curve for two gaussian distributions with equal variance

I recall a simple formula in a paper which relates the distance between two gaussian distributions (what psychologists refer to as d') to the ROC curve under the assumption that both distributions ...
1
vote
0answers
10 views

Random Forest: Class specific feature importance

I'm using the bigrf R-package to analyse a dataset with ca. 50.000 observations x 120 variables, classified into two groups. After growing a forest of 1000 trees, ...
1
vote
1answer
17 views

Fail to improve recall in classification

I have a large data set with over 700,000 examples and I tried to (binary) classify the data set with Naive Bayes and Random Forest. The task was carried out in Python and Scikit-learn data The data ...
0
votes
0answers
18 views

Data sets for which PCA can classify better than LDA (using a very small training set)

Can you provide an example of a dataset where PCA can find better discriminant directions than (LDA) Linear Discriminant Analysis? One example is UCI's wine data set. If you use only 2 observations ...
0
votes
1answer
29 views

Multinomial Naive Bayes is not Multinomial in text classification

According to Wiki, the Multinomial Naive Bayes's conditional distribution is: $$p(\mathbf{x} \vert C=k) = \text{Multinomial}(n,\mathbf p_k) = \frac{(\sum_d x_d)!}{\prod_d x_d !} \prod_d ...
0
votes
0answers
7 views

Techniques to improve GMM-based binary classifier performance?

I'm currently training a set of 2 GMMs (Gaussian Mixture Models) for 2 classes of data (stressed speech vs neutral speech), and making classification decisions by comparing the posterior probability ...
0
votes
0answers
14 views

For classification w unbalanced datasets, is class-weighing the same as oversampling?

in unbalanced classification problems, I find myself using class_weigh = "auto" or similar parameters often, but I don't think I'm fully understanding what it's doing. I know that it's the industry ...
1
vote
1answer
56 views

How to classify an empirical distribution into a group

How can I check that an empirical distribution function belongs to a group of empirical distribution functions? Imagine I have some customers who have been classified into some groups. Each person ...
0
votes
2answers
19 views

How to analyse the accuracy and standard deviation of a neural network in matlab toolbox? [on hold]

I am new in Matlab and neural network, and I am doing a prediction with some data that I found on the internet to learn more about it. Here is my function to create a neural network: ...
0
votes
0answers
9 views

What is the best way to analyse data comparing one by one and stipulate the accuracy?

Follow the example: The first line is the data I got. The second line is the target data. | 154.0 | 784.4 | 854.1 | 789.3 | | 153.5 | 789.7 | 892.3 | 903.2 | I ...
0
votes
0answers
9 views

understanding accuracy assessment of classification

I want to classify an image and I want to know how well I did, but I am not sure if I understand the workflow properly. I use scikit-learn. I first use cross_validate and GridSearchCV to find the ...
0
votes
0answers
24 views

Logistic regression in R, basing on which class(0 or 1) in dependent variable the modelling is performed

In R and in binomial logistic regression to be specific, the modelling is based on which class amongst 0 and 1? And if it builds model based on 1 by default, is there a parameter or something in which ...
0
votes
1answer
33 views

Python/R Exploratory Data Analysis for Classification [on hold]

Are there preexisting functions in Python/R that create exploratory data analysis plots like the following:
1
vote
0answers
13 views

How to find the threshold that maximizes the F1 score?

I have a probabilistic, binary classifier. Is there any principled way to select the threshold that maximizes the F1 score? Currently I simply choose many different thresholds, apply them on some ...
0
votes
0answers
17 views

Naive Bayes - Good for Binary Data?

I have 92 observations with 92 variables. Every observation is a binary outcome (0=no, 1=yes), indicating if that observation co-occurs with a given feature in the feature set. I have 18 classes which ...
0
votes
0answers
14 views

working with entire census data of population distribution

i am working on the total population of a state using census data sets, please what statistical techniques can i use to analyse the data to test if the distribution of population within the state in ...
0
votes
0answers
10 views

Getting prob of class using naive bayes

I am trying to classify input with two classes, here is the simple code for the same. dino and crypto are two classes ...
0
votes
0answers
13 views

use of statistics in analysing census data [closed]

Good day everyone. Please I need your urgent assistance. I am about to write a research project on the topic: The Application of Geographic information Systems In analysing Census data with regards to ...
0
votes
1answer
48 views

Standardization before applying ANOVA?

I have a matrix where the rows are the data points (samples) and the columns are the features. It is a multiclass (4 classes) problem. On this data I want to apply machine learning classifiers. But ...
0
votes
0answers
8 views

Deep classification, training vs inference phase

As I have described in Deep classification, how to represent category as TF-IDF vector?. I am trying to understand more in detail and reproduce the Deep classification for large scale taxonomy ...
1
vote
0answers
14 views

Deep classification, how to represent category as TF-IDF vector?

I am trying to implement so called deep classification method described here. I am trying to replicate chapter 4.2, with category-based search. Unfortunately, I am not sure how should I represent the ...
0
votes
1answer
17 views

How to score the predictions of a classification model?

I have made a classification model using support vector machine for the classification of two classes.The model is giving probability score and decision value for the test and training set and also ...
0
votes
0answers
26 views

Label outliers for anomaly detection

I am trying to detect anomalies using unsupervised learning techniques. However, I have the problem that it is impossible to generate controlled anomalies to use as a test set. My idea is to discover ...
1
vote
2answers
44 views

“Non-naive” bayesian classification algorithms

Based on the problem description in this post: Relating parameters to a measured variable Based on a suggestion, I thought of studying the relationship between the parameters and a measured metric ...
0
votes
0answers
26 views

Classifier that learns provided by only positive examples?

I was wondering if any of you has ever worked with classification/regression using only positive examples (one class). I would need such a system. The basic idea is that it is going to accurately ...
1
vote
2answers
33 views

Online learning that “forgets” older aspects learned? (short-term memory)

I am looking for an online learning classifier that is highly adaptable and has only short-term memory. I need such a think in a object tracking system with high-dimensional feature vectors. Maybe a ...
0
votes
2answers
28 views

Which data transformation can improve the performance of MLP neural networks for classification?

I am trying to fit several MLP neural networks models with a single hidden layer using the caret R-package. My main concern now is in the preprocessing step. My train data features (16 in total) are ...
1
vote
1answer
23 views

Best technology for keywords to features mapping

Source data = free text ("It's fresh and juicy and sweet") Pre-defined "knowledge" = "fresh" -> quality of a fruit "juicy" -> quality of a fruit "sweet" -> quality of a fruit "sweet" -> quality of ...
4
votes
0answers
32 views

Information gain and mutual information: different or equal?

I'm very confused about the difference between Information gain and mutual information. to make it even more confusing is that I can find both sources defining them as identical and other which ...
3
votes
0answers
34 views

SVM with non-negative weights

An SVM classifier can be obtained by solving the following, $\arg\min \frac{1}{2}\|W\|_2^2 + C\sum_i \max(0, 1-y_i (W^T\mathbf{x}_i + b))$ where $W$ is the hyperplane (or weights), $b$ is the bias, ...
1
vote
0answers
13 views

Advantages of using multiple lstm s in deep network

What are the advantages, why would one use multiple lstm s, stacked one side-by-side, in a deep-network? I am using a lstm to represent a sequence of inputs as a single input. So once I have that ...
0
votes
1answer
43 views

Is ROC or PR curve only the overall performance measure for classification

We can use ROC or PR curve to access the performance of the classifier,especially on imbalance data. But it is a curve with parameter threshold, even if we get a high ROC or PR performance, which ...
0
votes
0answers
14 views

How to use KL-divergence in naive bayes classifier to weight features?

I have a dataset consisting of 4 classes. I have implemented the Gaussian Naive Classifier (in Matlab). In the training phase I calculate the mean and variance for each feature and each class as well ...
0
votes
0answers
19 views

How to use Weight vector of SVM and logistic regression for feature importance?

I have trained a SVM and logistic regression classifier on my dataset. Both classifier provide a weight vector which is of the size of the number of features. I can use this weight vector to select ...
3
votes
1answer
26 views

How to use log probabilities for Gaussian Naive Bayes?

I'm currently implementing a Gaussian Naive Bayes classifier. Of course if I'm doing classification by $$ \text{argmax}_{C_i} P(C_i)P(D|C_i), $$ then the probabilities can get very small. So I want ...
1
vote
0answers
30 views

Adjust p-values for multiple comparisons

I want to evaluate if a proposed modification M* to a base classifier M is better in terms of accuracy. Both, the base classifiers M and their respective modifications M* are tested on N datasets. To ...
0
votes
0answers
18 views

How can I get feature importance for Gaussian Naive Bayes classifier?

I have a dataset consisting of 4 classes and around 200 features. I have implemented a Gaussian Naive Bayes classifier. I want now calculate the important of each feature for each pair of classes ...
0
votes
1answer
43 views

Why is LDA considered to be a classifier?

I am new to machine learning and I was reading about dimensional reduction algorithms like LDA(linear discriminant analysis) and PCA. Currently I am using LDA to find the optimal dimensions that ...
0
votes
0answers
17 views

Gaze estimation, choosing algorithm and parameters

I am trying to build a program for estimating point of gaze on the computer screen from the x and y coordinates of the pupil centres from webcam video .(x and y coordinates correspond to pixel ...
2
votes
0answers
33 views

Fisher LDA is a Bayes Classifier?

I've been going over many material in classification algorithms, and it seems that under the constraint that the covariance matrices are the same for a two-class problem then classifying a vector $x$ ...
0
votes
1answer
28 views

Proportional odds logistic regression with nominal (unordered) categories

Suppose that you've got a logistic regression with multiple nominal outcomes that cannot be ordered in a theoretically meaningful way. Assume further, however, that the proportional odds assumption ...
2
votes
1answer
35 views

“One sided” classifier

Below was tried in R, but any general solution would be highly appreciated: I have 2 class samples (both classes are balanced). I want to create a classifier, where I only care about 1 class (So, if ...
3
votes
2answers
140 views

Which unsupervised classification method to use next if hierarchical clustering gave bad results?

Purposes I need to perform a classification of weather stations taking into account the characteristics of intra-annual variability of some two climate indicators. There are 613 sites with monthly ...
1
vote
1answer
18 views

Training lstm a sequence one item at a time

I am trying to train an lstm with a sequence and get the sequence classification for the whole sequence. I have sequences of varying length so I have one input neuron and I am feeding one item at a ...
2
votes
1answer
16 views

Comparing performance of a single classifier on two datasets

I'm using a single classifier on two different datasets, consisting of non-overlapping set of observations. The performance on one dataset is higher than the other, and I want to show that the ...
1
vote
2answers
89 views

What measure of training error to report for Random Forests?

I'm currently fitting random forests for a classification problem using the randomForest package in R, and am unsure about how to report training error for these ...
2
votes
0answers
20 views

Problems with classification in imbalanced datasets

I often read about the problematic of doing classification in imbalanced datasets and methods to address it. Namely, off-the-shelf classifiers learn to minimize some form of total miss-clasffication ...
0
votes
1answer
32 views

Feature selection in a “Noisy” environment

My first question - This might be a basic question but I have yet to find an answer; when choosing the features for my model, I have encountered certain features which are vectors themselves. (e.g. ...
0
votes
0answers
41 views

How to quantify performance of Linear Discriminant Analysis (LDA)?

I have implemented Linear Discriminant Analysis (LDA) for dimensionality reduction in C. But I don't know how to quantify performance of the LDA. Could someone help me?