Methods and principles of selecting a subset of attributes for use in further modelling
0
votes
0answers
6 views
Topic Extraction using Scikit. Get documents for the Topics
I was trying to get a NNF model work for Topic Extraction.
SCIKIT code http://scikit-learn.org/dev/auto_examples/applications/topics_extraction_with_nmf.html# works fine. But what i wanted was ...
8
votes
2answers
300 views
Test accuracy higher than training. How to interpret?
A ML newbie here.
I've a dataset containing at most 150 examples (splitted to training & test), with many features (higher than 1000). I need to compare classifiers and feature selection methods ...
3
votes
0answers
30 views
Which variables are driving correlations within groups
I'm running an analysis on a few data sets that each typically have 100-200 cases measured across 120-160 variables - something similar to looking at gene expressions. Each variable is a non-centered ...
2
votes
0answers
42 views
Can we use random forest for classification in combination with distance matrix between classes
With a colleague, we are working on a dataset containing ~5000 continuous variables for 120 individuals belonging to 8 classes.
We want to estimate the relative importance of each variable to explain ...
2
votes
1answer
112 views
+100
Select best set of binary variables for clustering known sample labels
I have a set of samples, for which I know the "true groups". For this samples I have about 200 binary variables, I would like to know a method to select the subset of variables, that gives me a ...
3
votes
0answers
52 views
Variable selection / Dataset reduction for large datasets (in R)
I'm working on a behavoural scorecard modelling exercise, and many of the decisions taken to date have been based on the experience of a consulting credit analyst (whose experience software-wise is ...
0
votes
0answers
8 views
How to find the tendency of a feature in decision trees?
I've trained a decision tree binary classifier and I have the most informative features based on the sum of information gain weighted by the number of samples at the node (scikit-learn ...
1
vote
0answers
17 views
Using MatchIt to match groups in a retrospective analysis
I am interested in using the R package MatchIt to preprocess my data as to obtain matched groups based on a predefined treatment variable. However I am facing a few issues.
The first issue is that ...
1
vote
1answer
30 views
Features selection using F-score for multiclass classification
I'm going to implement a feature selection algorithm, and I plan to use the F-score for because of its simplicity. The problem is that, the F-score is used for binary classification. How can it be ...
2
votes
2answers
128 views
Using LASSO from lars (or glmnet) package in R for variable selection
Sorry if this question comes across a little basic.
I am looking to use LASSO variable selection for a multiple linear regression model in R. I have 15 predictors, one of which is categorical(will ...
1
vote
1answer
30 views
Evaluating features and similarity measures
I am currently developing a classificator, which is supposed to classify into a number of classes. For this purpose I am
designing some features and similarity measures which I might use for a later ...
0
votes
1answer
87 views
AIC, BIC, DIC, model selection criteria
I am trying to understand the difference between these parameters, and their application. Was hoping to get some correction/clarification to my statements. I have a training set and cross-validation ...
0
votes
0answers
23 views
Comparison of feature selection algorithms
I have to compare some feature selection algorithms. Please suggest some study materials from where I can get the idea about the comparison method.
0
votes
0answers
16 views
Choosing prior distribution in LDA
how do you set prior distribution of K in LDA and can it be used for feature selection to improved selection accuracy of document. Abbey
0
votes
1answer
26 views
BMI at baseline & followup with exposure at baseline; model change or BMI at FUP? Control for BMI baseline?
For a prospective occupational cohort where everyone is exposed to one or more chemical agents, examining BMI at follow-up compared to a specific chemical exposure at baseline, is it necessary to ...
0
votes
0answers
12 views
Which features to extract for classifying segmented zones of an image into two classes “handwritten text” and “graphics”
I have some chemical document images segmented into different zones, some zones represents "handwritten text" and others represent "graphics". I want to classify this zones into two classes, one for ...
3
votes
0answers
64 views
How does LASSO select among collinear predictors?
I'm looking for an intuitive answer why a GLM LASSO model selects a specific predictor out of a group of highly correlated ones, and why it does so differently then the best subset feature selection.
...
0
votes
0answers
36 views
How many attributes to select for classification
I am aware that this question is vague, but after reading multiple standard books of the community, I am still wondering about the following applied problem.
Lets say I have a dichotomy problem and ...
0
votes
2answers
120 views
Feature Selection Packages in R
I am very new to R. I am learning machine learning right now.
Very sorry, if this question appears to be very basic.
I am trying to find a good feature selection package in R.
I went through Boruta ...
0
votes
1answer
72 views
Variable Selection in R: Choosing One Variable from Each of 3 Buckets of Variables
I have a regression model that looks like the following
glm.nb(formula = y ~ Gender + Age + x1 + x2 + x3, data = df)
In my problem, there are 20 possible choices ...
0
votes
1answer
68 views
feature selection vs feature extraction
As per my understanding in dimensionality reduction, Feature selection chooses a subset from a list of available variables and, Feature extraction transforms available variables into lower dimension. ...
1
vote
1answer
29 views
Finding similar users
I am working on a problem in the online advertising space. I am trying to identify consumers similar to the set of consumers who have bought a product in the past (have 'converted'). If I can identify ...
1
vote
0answers
13 views
Is there any meta-approach for variable selection based of measures of similarity between each two variables?
Is there any meta-approach ( or mayby I should say universal approach which works with different measures ) for variable selection which is based on similarity matrix which every entry ...
0
votes
1answer
39 views
Relative importance weight with cforest
I am new in using RF. I want to use it to compute the relative importance of the features. I found the weight is very small ("party" package, cforest). Is there anyway to get these weights in a range ...
0
votes
0answers
44 views
similarity of feature vector
What is a better measure of feature vector similarity, Euclidean distance or dot product/cosine similarity? I've read about cosine similarity being used with document vectors, but I've also seen ...
1
vote
0answers
19 views
Performance worse with new observations
I come from the computer science area but am new to machine learning / stats, so this question may be fundamental and easy.
I have time-series data (biological data), and, without getting into the ...
0
votes
0answers
22 views
Selecting features for text classification
I've been trying to improve the accuracy of my sentiment classifier. It basically uses n-grams of words as features for a Naive Bayes classifier. I've been using mutual information to select features ...
0
votes
1answer
63 views
Alternatives to glmnet for feature selection on data with lots of NAs
I have a surgical database in which there are approximately 100,000 observations and 200 features. Each observation corresponds to a separate patient while the features correspond to either ...
0
votes
0answers
14 views
How to get average two features from the front and next impressions of the current fingerprint impression?
I am working on a Fingerprint recognition scheme using Assembling Invariant Moments. At the time of feature extraction ROIs would be failed to acquire for computing the features, so we chose to ...
3
votes
1answer
124 views
Is it possible to compare two feature selections algorithms by cross-validations?
Assume I have two feature selection algorithms, A and B, which are developed based on SVM. I applied these two algorithms on the same dataset, a Liver Cancer dataset (400 features & 150 samples), ...
0
votes
0answers
48 views
Issues with sequential feature selection
I am trying to do some feature selection in gene expression data with 22215 features. I followed the tutorial here.
I initially applied filter method(ttest) to select the features having the best p ...
2
votes
2answers
121 views
Mutual Information based feature selection
Suppose I have a feature matrix $F = [f_1^T,f_2^T,...,f_m^T]$ whereby $f_j^T \in \mathbb R^{n_t \times 1}$ is the $j$th column vector of $F$ ($n_t$ is the number of different events/trials and $m$ is ...
1
vote
1answer
146 views
Issues with feature selection in matlab
I am trying to use sequentialfs to do some feature selection in matlab. I have huge dimensional data of 22215 features. When I tried to use sequentialfs with svm as classifier so that it selects the ...
0
votes
0answers
8 views
Issues in doing feature selection using sequentialfs [duplicate]
I am trying to do some feature selection on gene expression data using sequentialfs function of matlab. The number of features is huge around 22215. And I have around 20 examples only. Now when I use ...
-1
votes
1answer
25 views
what are the dependent and independent factors and categorical for below project [closed]
my project is identification of factors influencing motor bikes for home to office trip. there are some attiributes like gender,age,marital status,education qualification,job type,working sector, no. ...
5
votes
2answers
129 views
What can cause PCA to worsen results of a classifier?
I have a classifier that I'm doing cross-validation on, along with a hundred or so features that I'm doing forward selection on to find optimal combinations of features. I also compare this against ...
1
vote
0answers
39 views
True and false discovery rate in variable selection
I have a question about how I can calculate true and false positive rate in a simulation study?
I have seen some articles and thesis by different definitions. One of them is the following one:
...
1
vote
2answers
75 views
Sparse hyperspace clustering
I have a dataset of M elements where every item is represented by a feature vector of length N where N is very large and only a small subset of N is bigger then zero for every item. So I have a sparse ...
3
votes
1answer
65 views
Variable importance randomForest negative values
I am asking myself if it is a good idea to remove those variables with a negative variable importance value ("%IncMSE") in a regression context. And if it gives me a better prediction? What do you ...
0
votes
0answers
57 views
How to perform step() when n < p in R?
I am trying to perform stepwise regression for variable selection in R.
In matlab, the stepwisefit function is able to work in ...
2
votes
0answers
34 views
Why do correlations matter in simulating data to compare classifiers when p >> N?
In genomics and computational biology, expression data sets contain a much larger number of features (p) than the number of observations (N). I wanted to simulate data where p>>N to compare the ...
1
vote
1answer
151 views
Using Adaboost for feature selection?
Is it okay to use Adaboost to do feature selection (selecting a subset of dimensions $S$ from a high-dimensional feature vector $V$)?
I divided the samples into four non-overlapping sets: $A$ ...
2
votes
1answer
62 views
A buggy but effective feature?
Through error analysis I found that a quite effective feature actually has bugs in its implementation. Correcting the bugs actually decreased the classifier's performance.
What do you do? Correct the ...
1
vote
0answers
38 views
How do I know if the differences in ICs among candidate models are significant?
I'm doing some exploratory modelling on a data set with 29 covariates and an additional 11 variables that are of interest to my research question.
My strategy is to develop a model with a subset of ...
5
votes
1answer
253 views
Bayesian variable selection — does it really work?
I thought I might toy with some Bayesian variable selection, following a nice blog post and the linked papers therein. I wrote a program in rjags (where I am quite a rookie) and fetched price data ...
0
votes
0answers
40 views
Feature Extraction
I have some tweets labelled as religion and education. I want to extract features from them so that I can make a model to predict future tweets. Can someone please suggest something??
3
votes
1answer
126 views
LASSO vs forward selection
I have two questions:
I use cross validation to select a LASSO model, does the step in which a particular variable enter, indicate its relative importance?
Let's age enter in step 1 and sex enter in ...
6
votes
4answers
225 views
Features for time series classification
I consider the problem of (multiclass) classification based on time series of variable length $T$, that is, to find a function
$$f(X_T) = y \in [1..K]\\
\text{for } X_T = (x_1, \dots, x_T)\\
...
0
votes
0answers
68 views
pathClass package R SVM-RFE
In several literature; its been published that Support Vector Machine performance can be enhanced if the features are carefully chosen. I am trying to do the same using R package "pathClass" using the ...
0
votes
0answers
98 views
Interpreting Results of InfoGain Attribute Evaluator in WEKA
I have run the InfoGain+Ranker algorithms in the Feature selection tab of the Weka in order to determine the significance of each individual variable that contributed to classification results. This ...
