Methods and principles of building "computer systems that automatically improve with experience."

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Choosing the most suitable similarity metric

Which of the following is the most suitable for calculating similarity between texts about 145 character long? Damerau-Levenshtein distance Levenshtein edit distance Sorensen-Dice coefficient ...
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12 views

How can 1 more feature disrupt a Random Forest's confusion matrix?

I'm trying to predict a binary variable with both random forests and logistic regression. I've got imbalanced classes (approx 1.5% of Y=1), so i'm calling ...
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8 views

How does svm deal with new level acquisition of a time series variable?

I am trying to predict customer spending for an X year period after t0. I train an svm model with transactions occurring before and on t0, on the cumulative spending of the customers after t0. I then ...
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18 views

Help With Application of Temporal Difference Learning

I'm trying to implement a $Q(\lambda)$ algorithm from this paper (warning: link is a download of a PDF) and can't seem to get it to find anything that close to the optimal policy. If possible, I'd ...
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1answer
27 views

Does a theoretical “perfect (accuracy) score” exists we could target for a given dataset?

My question is the following : You have a dataset, and you want to determine theoretically what accuracy score (or other way to measure performance such as AUC, etc.) a "perfect" model could get on ...
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6 views

Use known output distribution to increase maxent classifier performance

If you know the distribution of your output, can you use this information to improve the performance of a maximum entropy classifier? e.g., I know that a gallery of pictures is 40% cats, 60% ...
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29 views

Regression models to only predict integers (instead of floating point numbers)?

I have a dataset that consists of about 50 different attributes. One of these attributes I want to predict, using the other attributes as features. The values of the attribute that I want to predict ...
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17 views

Do we need gradient descent to find the coefficients of a linear regression model

I was trying to learn machine learning using the coursera material Andrew Ng uses gradient descent algorithm to find the coefficients of the linear regression model that will minimize the error ...
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9 views

Reference request machine learning [duplicate]

I recently found out what's Machine Learning, I've signed up for a course of an online platform to learn the basics, and next semester I will take a course about it at my university. But I would take ...
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3 views

Is there a classified corpus to learn similarities in a citation network? [on hold]

I am trying to train an ML algorithm to calculate the topic similarity of scientific papers based on their structural similarity in a citation network (i.e. a graph where vertices are scientific ...
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3answers
1k views

Is automated machine learning a dream?

As I discover machine learning I see different interesting techniques such as: automatically tune algorithms with techniques such as grid search, get more ...
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10 views

How do I use Hidden Markov Model Viterbi algorithm for sequence labeling?

with my current small experience of HMM. Given that i have some patterns (sequence of interest for example gestures or words in spoken language) if i need to use HMM for sequence classification ...
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1answer
16 views

Unconnected Linearly Seperable Classification

Consider classifying something like the case shown below (exagerated syntetic example): If this were a task to classsify into 3 groups, (blue-left, red, blue-right), then a Linear Support Vector ...
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5 views

Structural Correspondence Learning for Domain Adaptation - how is the augmented data formed?

Structural Correspondence Learning (SCL) is a method for dealing with domain adaptation (different data distributions in the training and testing sets). It was proposed by Blitzer et al. but I am ...
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2answers
26 views

Are fixed bias neurons or biased neurons better?

When building an artificial neural network, there seems to be two differing philosophies in usage of biases. There are those groups that propose neural networks with a fixed bias neuron with a ...
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10 views

Softmax Regression GD Update Derivation

I'm implementing softmax regression and am deriving the max-log-likelihood update for gradient descent by hand first. Coming from the Stanford UFLDL site, they show the gradient of the cost function ...
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1answer
15 views

how to interpret metrics for my model

I understand how these metrics are determined but can anyone give me typical poor, acceptable, good, and outstanding values RAE and RSE?
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1answer
28 views

How to do one-vs-one classification for logistic regression?

I have a dataset with 4 clases and I want to apply logistic regression with one-vs-one classification. So, first I train for each pair of classes a logistic regression classifier (i.e. calculate the ...
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1answer
31 views

Adaboost for numeric dataset

I have been trying to fit Adaboost to work with continuous valued data set and the more I read the more I keep getting confused. I have read about the multiclass Adaboost with log(K-1) addition to ...
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16 views

How can you detect outliers in a group of face images?

I'm trying to filter an image database which contains some irrelevant pictures. All the faces are labeled with points around the face contour, eyes, mouth, eyebrows, have age and gender. The faces are ...
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10 views

Training and Activating a 2 layer deep network

I've been working with synaptic.js to make neural-networks in the browser for a while and I've decided I want to implemented deep-learning for a project I'm working on ( connecting an lstm to a ...
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12 views

what exactly is projected gradient descent?

I am reading the article with title "metric learning by collapsing classes" http://papers.nips.cc/paper/2947-metric-learning-by-collapsing-classes.pdf.There are some questions which has bothered me ...
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1answer
61 views

What are the differences between Ridge regression using R's glmnet and Python's scikit-learn?

I am going through the LAB section §6.6 on Ridge Regression/Lasso in the book 'An Introduction to Statistical Learning with Applications in R' by James, Witten, Hastie, Tibshirani (2013). More ...
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1answer
20 views

Data splitting using kennard stone [on hold]

I would like to use kennard stone algorithm for splitting a dataset into training and test set. Does Weka /Rapidminer/any free software with GUI has a feature to do this? If so, would like to know the ...
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1answer
34 views

Why is the energy and the probability of a configuration related in a Boltzmann machine?

According to Hinton's slides (slide 34) the following relationship holds for Boltzmann Machines in thermal equilibrium: $$ p(v,h) = \frac{e^{-E(v,h)}}{\sum_{u,g}{e^{-E(u,g)}}} $$ To me this is not ...
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34 views

How is bootstrapping used for machine learning?

How does one use bootstrapping in a machine learning context? My typical data analysis pipeline is Split data into 10 folds Train classifier with 9 folds Test classifier with remaining fold Repeat ...
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22 views

Get important features of n samples

Suppose I have a data frame of [n_samples, m_features] with the corresponding variances of the features [n_features]. The values in my data is between 0 and 1 so the question is: Is there any way to ...
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23 views

How can I make Weka classify the smaller class, with a 2:1 class imbalance?

How can I make Weka classify the smaller classification? I have a data set where the positive classification is 35% of the data set and the negative classification is 65% of the data set. I want Weka ...
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21 views

Time-series cross-sectional classification problem

I have a time-series cross-sectional dataset consisting of 100 individuals that each had 4 features measured yearly for 21 consecutive years. One of the features is binary and the other three are ...
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8 views

How can I use Extreme Learning Machine in Rapidminer? [on hold]

I am working on a problem, I need to use 'Extreme Learning Machine.' But I don't know any programming language. I use Rapidminer. Is it possible to use the algorithm on Rapidminer?
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19 views

Representation of misspelled words for neural network?

While thinking about a neural network based spellchecker, I was thinking about word embedding not being able to represent any "unique" (misspelled) words that the model haven't seen before. I tried ...
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how can fixed parameters cost and gamma using libsvm matlab to improve accuracy? [migrated]

I use libsvm to classify a data base that contain 1000 labels. I am new in libsvm and I found a problem to choose the parameters c and g to improve performance. First, here is the program that I use ...
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7 views

Regarding pattern recognition and forecasting next set of sequence [closed]

I have been working on use case where I have some sample data as below : Date Device Name Time Facility Code 1/6/2015 Tablet X 16:18:48:168 22 A 1/6/2015 Tablet X 16:18:50:41 ...
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24 views

Kernel K nearest neighbours with sparse data

I have a big sparse matrix (around 5 million of lines, 20 000 predictors), and I would like to run a kernelized k-NN on it. However, I don't know how to scale the data properly. So far, I have scaled ...
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1answer
63 views

Improving a logistic regression model in R [closed]

I have to devise a model in R, capable of predicting the type of a disease, which is a categorical dependent variable (three possible values), through several continuous and categorical, some of the ...
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8 views

mahout kmeans class not found exception [closed]

I have configured Hadoop in Psuedo-Distributed mode. I have succesfully created sequence-files and tf-idf vectors(using seq2sparse) and am trying to run mahout kmeans from command-line as follows: ...
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14 views

What techniques infer dependencies between time series?

I'm working on an ML project. We have an app where users can track 1) binary variables and 2) quantities over time on a scale from one to ten. For example, at a given time they may track whether they ...
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13 views

VC Dimension of the set of canonical hyperplanes

This is a proof of the theorem about VC Dimension of the set of canonical hyperplanes from Professor Mohri's lecture slide. I'm having difficulty with understanding the inequality$$ \forall i \in ...
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23 views

Upcoming areas in theoretical Bayesian Machine Learning [closed]

I will soon be going for a postdoc position at a new university. One thing that the panelist asked me to think of is if I were to start, what would I work on. Now the thing is so far with my PhD ...
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8 views

RSNNS neural networks, checking percentage correct.

For those who have some experience with RSNNS, I'm trying to build a neural network for reading aloud, using RSNNS in R. To give some information about what I'm doing and using. I'm using orthographic ...
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1answer
18 views

Is there a difference between on-line learning, incremental learning and sequential learning?

What I mean is the following: Instead of processing all the training data at once and calculating a model or hypothesis, we process one data point at a time and update the model directly afterwards. ...
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7 views

How should I measure difference between user behavior / model performance on different population?

I am developing a recommendation engine whose goal is to suggest data exploration routes to non-technical users. The underlying model is content based, with the training data made up of the behavior ...
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16 views

How to use Particle Swarm Optimization for finding optimal bandwidth with cross-validation?

I want to use Particle Swarm Optimization (PSO)for finding optimal smoothing parameters of a kernel density estimation problem. Initially I tried to find the same using grid search method,but the ...
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8 views

Touch times to authenticate user

for a project I gathered touch data of different users when they tap a rhythm repeatedly on the touch screen in a game. ...
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0answers
63 views

how to solve an optimization problem? [closed]

I am reading an article with title "Learning a distance metric from relative comparisions" lately. http://www.cs.cornell.edu/people/tj/publications/schultz_joachims_03a.pdf. The basic idea for this ...
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9 views

Scikit Random forest pred_proba gives rounded off values

I am using random forest in scikit learn for classification and for getting the class probabilities , I used pred_proba function. But strangely it outputs probabilities rounded to first decimal place ...
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2answers
32 views

Name some techniques similar to Random Forests

I'm interested in what techniques are out there that are similar to, but not the same as, Random Forests. Either for classification or regression or both. Particularly interested in techniques which ...
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SKLearn Clustering: how would you cluster a LARGE database of dogs? [closed]

Given: A VERY large dataset of dogs. columns: ID (alphanumeric) Weight (numeric) Height (numeric) Eye Color (alphabet) ... (numeric) Tongue Length (numeric) How do you find what makes these ...
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41 views

Fitting a trading model [closed]

I have a high frequency time series of the bid and ask prices of a stock recorded on every tick. For each data point I also have a certain indicators that predict the future movement of the price. The ...
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1answer
37 views

Weight shrinking in linear regression by L2 regularization

Quoting Prof. Bengio from his Deep Learning text (http://www.iro.umontreal.ca/~bengioy/dlbook/regularization.html), $ w = (X^{T}X + \alpha I)^{-1}X^{T}y $ We can see L2 regularization causes ...