Methods and principles of selecting a subset of attributes for use in further modelling

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Feature boosting via rescaling in logistic regression and linear SVMs

If I were expressing a problem in terms of binary features, all encoded as {0,1}, could I boost some features by encoding them as {0,2}? Would the effect change based on whether I used either of the ...
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80 views

Mutual information/pointwise mutual information for measuring prediction

I want to measure how well I predict a vector $Y$ (vector not a label) for observation $X$. Both $X$ and $Y$ have the same set of features ($1\times n$). For that, I thought of "scoring" the ...
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Statistical test for feature selection

Suppose I have a procedure to select K features out of M. I repeat the procedure N times on, say bootstrapped datasets, and count how many times feature #1 appeared among selected, denote k1, how many ...
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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 ...
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2answers
76 views

Choosing the best featureset for prediction

I have this N sets of features F each with $F_i$ number of features. All the feature sets have 20000 examples and we have 20,000 labels for them. Lets say feature set $F_1$ has 10 features and ...
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4answers
85 views

Interpreting conflicting results from Random Forest & Logistic Regression?

I am using SKLearn and Statsmodel in python to build a RF and Logistic Regression, respectively. I have a feature that the RF indicates is important (feature importance of 0.202, closely behind #1 ...
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1answer
814 views

Clustering probability distributions - methods & metrics?

I have some data points, each containing 5 vectors of agglomerated discrete results, each vector's results generated by a different distribution, (the specific kind of which I am not sure, my best ...
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17 views

Select the best point pair in the 2D grid [duplicate]

Suppose in the 2D space we have an array of points, and each point has a weighting factor, which is a float value ranging from 0 to 1. Each point also has a coordinate in the 2D grid. The following ...
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2answers
55 views

Why isn't the lasso selected variable even not significant?

I performed a lasso selection using lars::lars for a well normally distributed outcome using a pool of 86 predictors. Here is the plot of the output: The ...
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1answer
69 views

Feature selection for pattern mining

I must find frequent patterns in temporal data, using a method that was imposed to me. This tool has problems handling these data: processing is long and takes a lot of memory. So, I would like to ...
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1answer
94 views

Random forest cross validation for feature selection, imbalanced datasets

I have an 5297X26 imbalanced dataset, the class1 has 588 samples and class2 has 4709 samples. I used the following code to perform random forest: ...
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1answer
103 views

How to find important features in this problem

I was just thinking how ML techniques can be applied in the retail industry. Suppose we have data from a retailer who deals with apparel and cloth in this format and for each item there are ...
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1answer
30 views

Handle large set of features using SVM

I have a biological dataset with 30.000 features (genes) and 1000 data points (cells). Basically I have two major classes of cells: 1 and 0 with a distribution of 90/10. Now I am trying to classify ...
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1answer
342 views

What is a good Gini decrease cutoff for feature inclusion based upon random forests?

I am using random forests to try and determine variable importance as part of feature selection for a model I'm working on, and while I can get ranked variable importance by mean decrease in Gini from ...
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469 views
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18 views

How to deal with categorical features.

Recently I am playing in the famous Big-Data website Kaggle. There is a Display Advertising Challenge. In this competition, you are giving a training file which include huge records. the records is ...
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6 views

libsvm with diffrent count of Keypoints [migrated]

I would like to use libsvm for a keypoint detection algorithm. Each keypoint has 36 features, but each sample of an Object has a diffrent count of keypoints... Is it even possible to train with ...
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1answer
151 views

Determining conserved features using a Bayesian approach

I would like to perform some sort of binary classification, and my data set consists of 100 examples (for each class), which are vectors with 2500 elements. Ideally, I would like to determine which ...
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4answers
1k 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)\\ ...
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1answer
202 views

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 ...
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feature selection for longitudinal data

I have a longitudinal data which looks like this. Number of time points are different for each ID. Y is the binary response variable (take values 0 & 1) and X1-X20 are either continuous or ...
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2answers
78 views

Methods in R or Python to perform feature selection in unsupervised learning

What are the available methods/implementation in R/Python to discard/select unimportant/important features in data? My data does not have labels (unsupervised). The data has ~100 features with mixed ...
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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 ...
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1answer
34 views

How to normalize time series?

This is a general question on normalization of data so that all the variables are within the same range. Why do we normalize data in pattern classification? How to normalize time series which is ...
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8 views

Does within-group heterogeneity negatively impact random forest classification?

I have two rather conceptual questions about random forest classifiers. Before we get there, I quickly want to lay out the problem I am working on: I have large a large data set consisting of 300 ...
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23 views

Triple nested cross validation

I have read several very informative posts including the link about the nested/double cross validation, which can determine (sub)optimal hyperparameter values as well as make an unbiased estimate of ...
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2answers
73 views

Advice for interpolating a model

I'm new in Stack Exchange, so I hope no to be off topic. I'm also new in bioinformatics and I was asked to perform an analysis. Briefly, I have a dataset of 29 cell lines and the IC50 values of a test ...
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27 views

Find linear SVM feature weights using libsvm

I'm trying to use linear SVM to do some feature selection. I'm using libsvm, but I cannot figure out how to find feature weights. The model file created looks something like this: ...
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14 views

Considering non-i.i.d. covariates in random forests

Random forests are theoretically funded on the assumption that the data are i.i.d. realizations from a multivariate random vector $(X_1, \ldots, X_p, Y)$. Does it make sense to use random forests (for ...
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135 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 ...
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1answer
83 views

Extract important features

Here is my situation: - A huge amount of data - 600 features - Only one class is provided Now, my question is how can I reduce the number of features to important ones? In another word, all of these ...
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22 views

How to deal with a feature relating to what type of expert labelled the data that becomes unavailable at point of classification?

Essentially I have a data set, that has a feature vector, and label indicating whether it is spam or non-spam. To get the labels for this data, 2 distinct types of expert were used each using ...
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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 ...
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4answers
182 views

Lasso-ing the order of a lag?

Suppose I have longitudinal data of the form $\mathbf Y = (Y_1, \ldots, Y_J) \sim \mathcal N(\mu, \Sigma)$ (I have multiple observations, this is just the form of a single one). I'm interested in ...
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1answer
38 views

Predictive features with high presence in one class

I am doing a logistic regression to predict the outcome of a binary variable, say whether a journal paper gets accepted or not. The independent variable or predictors are all the phrases used in these ...
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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 / ...
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1answer
116 views

How to use rfe object with function pickSizeTolerance in R package caret

I run caret's recursive feature selection with randomForest. While running rfe function with method repeatedcv, I had parameter ...
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7 views

chi-squared feature selection

I have a feature vector of size 250 x 35. That is I have 250 images and each image has 35 features in it. I need to do chi-squared test to get the most significant features out of it. anyone know ...
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1answer
26 views

mixing binary and real-valued features with SGD

I'm going to be using a logistic regression model and using SGD to determine the feature weights. Is it OK for me to use a mix of binary and real features, without doing anything like scaling or ...
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1answer
13 views

Feature selection with a binary dependent variable

Given we have a binary dependent variable and 100s of features and ~50k observations, is there a generally accepted way to trim the features via some type of machine learning concept? I was trying a ...
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How to: cross validation and scaling features using LibSVM – binary classification problem

I have a matrix of samples in rows and features in columns. I want to train this data matrix using LibSVM. How can I normalize or scale my features before running LibSVM? How can I perform cross ...
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1answer
27 views

Which feature selection method to use for classification problem

I have to do some feature selection for a classification problem with numeric features. I am not sure which feature selection method to use. Chisquared test or Spearmann's rank correlation ...
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15 views

On population variable importance

Consider we run a random forest on $n$ independent realizations of a random vector $(X_1,X_2,X_3,Y)$ assuming $Y$ is a numerical response variable. Let $f$ be the best theoretical classifier defined ...
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Featuring Engineering from Trends in the Training Set

I have a predictive model with just OK performance, and I'm trying to improve it with feature engineering. My question: is it valid to create new features by looking at trends in the training set? ...
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9 views

When to cluster features for supervised learning?

I'm doing a project on dog adoption patterns, and I realized that there are many (100 +) different breeds of dogs. I'd like to build a predictive model using breed as covariate, but I'm not sure ...
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2answers
52 views

What interactions to include in my GLM model?

I realize this might be a too general question, so I'll describe what I'm doing right now first. I'm working for a virtual insurance company and I have this dataset. It has severity (meaning ...
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1answer
27 views

Caret: customizing feature selection, nested inside cross validation

Using caret, I want to train a SVM classifier and estimate its performance using repeated cross validation. My dataset has a very large number of predictors (300K) and I want to reduce this number ...
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5 views

Design a feature with time and presence information

Context: I am working on a decision tree classifier, trying to classify businesses as to whether they are likely to have an event occur (default) in the next 90 days. One input I get is whether, and ...
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1answer
56 views

finding an optimal subgroup of binary indicators

My dependent variable is continuous variable that measures the (potential) success of a person in some activity. I have hundreds of binary indicators, each indicates about the existence of a specific ...