The tag has no wiki summary.

learn more… | top users | synonyms

1
vote
1answer
37 views

Feature engineering

I recently realized, that feature engineering (designing input vectors for machine-learning algorithm) is one of the most complicated tasks when applying known algorithms (for example kernel ...
1
vote
0answers
9 views

Principled way of collapsing categorical variables with many categories

What techniques could I use to optimize the collapsing of many categories to a few, for the purpose of using them as an input to a statistical model? Consider a variable like college student major. ...
-1
votes
0answers
14 views

embed histogram into larger feature vector

in my problem I have feature sets extracted by different methods and I want to put them into one single feature vector. However, one of these feature sets is a histogram which I don't know what's the ...
0
votes
1answer
24 views

Classifier with variable number of features

I am trying to make a classifier when each sample has a variable number of features. An example of how this could occur is, for example, if the features are the purchases (type, dollar amount, etc) ...
1
vote
2answers
61 views

How To Better Represent A Problem To A Machine Learning Algorithm

I am familiar with the basics of how to present a problem to a machine learning algorithm using binary encodings. I am also familiar with, but still learning about, feature selection/extraction and ...
1
vote
1answer
14 views

What kind of general strategy can you apply after selecting model and hyper parameter training?

As a rookie to machine learning area, I tried to play some Data Science tutorials and beginner competitions to gain some knowledge and experience. The problem I encountered in every scenarios is ...
0
votes
1answer
23 views

How much prediction accuracy of SVM (or other ML models) depend on the way features are encoded?

Suppose that for a given ML problem, we have a feature which car the person possesses. We can encode this information in one of the following ways: Assign an id to each of the car. Make a column ...
1
vote
0answers
21 views

Learning if instances from a dataset are part of the same subset

I was wondering if there are some well-known machine learning methodologies for subset learning. In other words, to learn if two instances are part of the same subset or not (boolean label?). One ...
0
votes
1answer
35 views

Useful Representation of Continuous and Nominal variables

I want to develop a prediction model (e.g. using SVM, Neural Networks...etc) to predict the relationship between a protein and its DNA target. Each proteins is represented using ~100 continuous ...
6
votes
4answers
139 views

How to prepare/construct features for anomaly detection (network security data)

My goal is to analyse network logs (e.g., Apache, syslog, Active Directory security audit and so on) using clustering / anomaly detection for intrusion detection purposes. From the logs I have a lot ...
1
vote
1answer
46 views

How to do machine learning (regression/classification) when the samples are of different sizes?

In standard cookbook machine learning, we operate on a rectangular matrix; that is, all of our data points have the same number of features. How do we cope with situations in which all of our data ...
0
votes
1answer
35 views

Automatic feature building/extraction

I have a large time stamped data set (several millions of rows), with known measured inputs xi, where i is a large number to the order of magnitude of 20. The goal is to predict a response yi given ...
0
votes
0answers
9 views

Need to order a set of colors to build a feature vector

I am working on Computer Vision task of object classification with python and OpenCV. Currently I am extracting some characteristic colors of an image using K-means clustering on all the pixel to ...
0
votes
0answers
11 views

Is there an algorithm to determine if too few features are selected for k-nearest-neighbor?

Is there an algorithm to determine if too few features are selected for k-nearest-neighbor when no test set is available, --when the input vectors are unknowns? Here's my problem, I have a massive ...
2
votes
2answers
179 views

Machine learning feature encoding

I'm new to Machine Learning. I've just finished the Coursera course. :) And for my first practical attempt I wanted to "analyse" a local used cars selling website in order to compose a modal that ...
0
votes
1answer
28 views

Using a set as a feature in decision tree classification

I'm faced with a data set where one of the features is a set of 4-5 categories (this number of categories isn't constant). I need to use this feature for building a decision tree. I searched online ...
1
vote
0answers
22 views

Statistical technique for data when three interventions are administrated and multiple responses measuring different constructs are measured

I have a data where three interventions were administrated on subjects and different response variables (say 15 variables) on Likert Scale were observed. These response variables measure three ...
5
votes
2answers
405 views

Autoencoders can't learn meaningful features

I have 50,000 images such as these two: They depict graphs of data. I wanted to extract features from these images so I used autoencoder code provided by Theano (deeplearning.net). The problem ...
0
votes
1answer
45 views

pairwise distances used as features for classification

I have a feature matrix 977x3 features = rand(977,3); where each row is an observation and each column is a feature. I calculate the pairwise distances between ...
0
votes
0answers
38 views

DecisionTreeClassifier scikit-learn : knowing the leaf to which an example belongs to

I am currently reading this paper http://quinonero.net/Publications/predicting-clicks-facebook.pdf , where they are using trees to generate feature that are afterwards fed to a linear classifier. My ...
3
votes
1answer
72 views

Optimal construction of day feature in neural networks

Working on regression problem I started to think about representation of "day of a week" feature. I wonder which approach would perform better: one feature; value 1/7 for Monday; 2/7 for Tuesday... ...
1
vote
0answers
33 views

What's the potential reason that by combining two feature sets the performance of random forest dropped?

I am building random forests on high dimensional, sparse, and class unbalanced training datasets (around 500 - 5000 examples) using two different feature sets. I did stratified 10-fold cross ...
1
vote
1answer
84 views

Convolutional neural network - Using absolute of tanh on convolution output

I've watched an online lecture regarding CNN (https://www.youtube.com/watch?v=wORlSgx0hZY) that confused me a bit. At roughly 8:35 in the lecture it was stated that it is important to use the absolute ...
0
votes
1answer
56 views

NLP tokenization for building feature vector

I am trying to match new product description with the existing ones. Product description looks like this: Panasonic DMC-FX07EB digital camera silver. These are steps to be performed: Tokenize ...
3
votes
0answers
57 views

Placement of earlier features in more complex features in CNN

I'm trying to understand convolutional neural networks better. I've been doing different tutorials, but there are some basics concerning how the hidden units represents features that I really would ...
0
votes
0answers
30 views

Hashing functions in NLP

I have been reading a lot of papers about nlp which use the hashing trick, and I came across a lot of sentences like : "We take k hashing functions to hash words or bi-grams". And after that they ...
1
vote
0answers
46 views

How can I make sure that an LDA implementation works?

I am currently experimenting with neural nets for classification of on-line handwritten data (hence: not pixels, but time series data). To do so, I use several toolkits (internal development of my ...
1
vote
0answers
13 views

Aggregating features on time from individual samples

I am trying to solve a problem in which I need to figure out what is driving the daily/monthly total expenditure up over time. The data I have is something like this, ...
1
vote
0answers
38 views

Reduction of sparse features for machine learning

I'm trying to use a 1D histogram as a feature for machine learning. A histogram instance can be very sparse and the range of its bins is theoretically unbounded. Moreover it is expected that non-zero ...
0
votes
0answers
110 views

Extracting fixed-length feature vectors from variable-length time series

I have a classification problem where I would like to develop a binary classifier to classify between two different types of objects, given a time-series (signal) related to that object. The problem ...
1
vote
1answer
54 views

How can I calculate cosine distance with multiple feature vectors and weigh them?

I have a dataset of text documents and I'm calculating pairwise cosine distances among them. For each document I have a bag of words vector, a vector built from entities extracted from the document, ...
0
votes
1answer
22 views

How to use a set attributes of an entity at different time snaps to make predictive analysis?

The problem is to come up with a classifier for any task based on a set of attributes of an entity having different values at different times. For instance think about football players and their match ...
0
votes
0answers
24 views

Optional Features

I'm trying to get my head around what I call "optional features" but since I don't know their proper name in statistics I can't find any information about them. Essentially, I'm looking at a problem ...
0
votes
0answers
29 views

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? ...
0
votes
0answers
13 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 ...
0
votes
0answers
6 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 ...
1
vote
0answers
26 views

Walking recognition

I have walking samples from 20 different people. My aim is to detect which walking samples are from which person. I'm trying to achieve this by extracting "walking cycles" from each person's dataset ...
0
votes
0answers
32 views

Mixing Categorical and Continuous variables where cardinality of categorical can surpass data points

Suppose we have a dataset of people that can be described with a mix of some continuous variables (eg height, age) some ordinal (eg social status) and some categorical (eg city, car brand, favourite ...
2
votes
1answer
62 views

What's the optimal way to encode a 'month' feature?

What's the optimal way to encode a 'month' feature? A single integer value or 12 binary values don't quite grasp the concept of modulo distance... Say I want to train an SVM for a certain task and ...
0
votes
1answer
51 views

Quantifying Change in a Histogram Valued Timeseries

I'm attempting to do binary classification where my raw features are collections of histograms that are recorded in a time series. These histograms are scaled to sum to 1. To be more precise and ...
0
votes
0answers
4 views

how to measure the model recovery performance

I have some simulated linear model $y = X\beta+\epsilon$ where $\beta$ is sparse. I am comparing different techniques to recover the structure of $\beta$. I have so 4 values True Positives, False ...
2
votes
3answers
214 views

Best way to turn a date into a numerical feature?

I have a fairly large dataset with a few fields containing time-related data. This data comes in various shapes and sizes, but most of it can be parsed and rephrased in more appropriate formats for ...
1
vote
0answers
48 views

Computing directly comparable wavelet features on variable-length training examples

Consider a classification problem in which the raw data are snippets of a larger 1-D time series signal. In my application, the signal is the response of a motion sensor as a function of time (the raw ...
0
votes
1answer
30 views

Importance of Time Features

if you have a time series and you want to do some predictions, what time feature should you use ? lets say we are trying to predict how many people visit a certain website, we have data for the ...
1
vote
1answer
33 views

Transform a non-monotonic value before decision tree (concrete example)?

Newbie question here. I am building a toy decision tree to differentiate personal names from business, government, or organizational names, like: AAA ENTERPRISES LLC DBA AAA BBB SERVICE SMITH ...
0
votes
0answers
63 views

How to prove the significance of features in classification?

I have a binary classification problem. I have extracted 500 features from a set of 5000 samples using my domain knowledge. In other words, I have got hand crafted features. I wish to prove that ...
0
votes
0answers
8 views

Redundant feature generation

I'm evaluating a few supervised feature selection algorithms, with a focus on redundancy. As a base correlation statistic, I'm using Mutual Information - so discrete variables are also a focus for ...
10
votes
6answers
602 views

how to represent geography or zip code in machine learning model or recommender system?

I am building a model and I think that geographic location is likely to be very good at predicting my target variable. I have the zip code of each of my users. I am not entirely sure about the best ...
1
vote
0answers
129 views

“Robust” normalization of features from multiple groups and unknown distributions prior to learning

I'm working on a machine learning project involving statistical analysis (and later discriminatory classification) of different proteins (samples) drawn from multiple, potentially overlapping classes ...
0
votes
1answer
27 views

feature representation for DNA bases classification

I'm currently dealing with large DNA sequences for machine learning purposes, I'm basically improving existing methods. What I have is several millions of DNA sequences : ACGTAGGCAGGCTTTC ... In ...