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

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has anyone tried to use spectrum kernel

Can any one explain me how to use string kernels to quantify the similarity between short texts? thank you. regards
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4 views

Meaning of “reconstruction error”

I am implementing PCA, LDA, and Niave Bayes, for compression and classification respectively (implementing both an LDA for compression and classification). I have the code written and everything ...
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1answer
195 views

Classification accuracy

I am classifying text based on news headlines and I am achieving accuracy up to approx 80%. I want to improve it more. But issue is that when I calculate the same with synonyms using the code below: ...
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5answers
680 views

Can anyone tell me why we always use the Gaussian distribution in Machine learning?

For example, we always assumed that the data or signal error is a Gaussian distribution? why? I have asked this question on stackoverflow, the link: ...
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3answers
1k views

LibSVM weights of support vectors

I am using LibSVM classifier in my Java code and I am getting correct results as I verified that with weka GUI, however, when I want to get the weights of the ...
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1answer
130 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 ...
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1answer
64 views

Figuring out Signal to Noise Ratio of Spectral data?

I have some Raman spectral data of a chemical: Each spectrum consist of multiple tuples of (wavenumber, intensity) I have multiple instances of ...
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1answer
278 views

Vehicle license plate recognition using Convolutional Neural Network trained with mnist data

I would like to construct a license plate recognition system using convolutional neural network (CNN). But I do not have appropriate dataset to train from. If I train my CNN on the MNIST handwritten ...
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0answers
15 views

What does make SVM a “soft computing” method?

Soft computing is defined in [1] by the capability of "operating with uncertain, imprecise and incomplete information in a manner that reflects human thinking". So, based on my limited understanding, ...
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1answer
2k views

Is R-squared value appropriate for comparing models?

I'm trying to identify the best model to predict the prices of automobiles, using the prices and features available on automobile classified advertisement sites. For this I used couple a of models ...
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2answers
22 views

Dynamical time warping for dynamical system classification

I am trying to find a way to classify and segment a large set of time series that each individually describe a dynamical system. I wanted to know if the following idea for doing so is a feasible ...
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0answers
52 views

xgboost binary logistic regression

I am having problems running logistic regression with xgboost that can be summarized on the following example. Lets assume I have a very simple dataframe with two predictors and one target variable: ...
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3answers
1k views

In machine learning, why are superscripts used instead of subscripts?

I'm taking Andrew Ng's course on Machine Learning through Coursera. For equations, superscripts are used instead of subscripts. For example, in the following equation $x^{(i)}$ is used instead of ...
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1answer
14 views

Computing the Interaction gain. Is there an Error in the infotheo package in R?

In order to implementing a certain feature selection method for a classification problem I need to estimate the the interaction the interaction gain between two features and the target variable which ...
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0answers
12 views

Is dimensional reduction using Autoencoders possible with a small sample size?

I have a data set that is not too big but high dimensional, let say 10000 dimensional. I want to use an autoencoder to extract relevant features (clusters) in the data. Usually when I have seen ...
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2answers
335 views

Question regarding parameters and variable selection in Mahout algorithm for logistic regression

Below is the list of parameters in Mahout logistic regression. What does "passes" mean? In detail please --passes passes the number of times to pass over the input data ...
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0answers
8 views

Need to understand the BenStuff_CrossValCorr [on hold]

First, I want a sample example of BenStuff_CrossValCorr Thanks. Dr R.baouche
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63 views

Using Association Rules found using arules package in R

I have used the arules package and used the Apriori algorithm to find numerous rules for my dataset. However, I struggle to put the rules use. I stumbled upon this post: Finding suitable rules for ...
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1answer
226 views

How to use Particle Swarm Optimization for finding hyper-parameters of Support Vector Regression?

I want to use Particle Swarm Optimization (PSO)for finding hyper parameters of a support vector regression problem. Initially I tried to find the same using grid search method,but the Matlab code is ...
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0answers
8 views

model to learn graph

I'm looking for machine learning techniques which allow me to obtain a model learning relationship of graphs. In a basic regression problem, model learns a relationship between real values. A model ...
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0answers
8 views

AdaBoost - How to use the distribution D [migrated]

I am trying to implement AdaBoost algorithm in Python. I have m weak classifiers in list called classifiers. I have vector _D ...
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1answer
124 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
18 views

clustering evaluation for a special case

In my dataset each point comes from one of 3 classes, so the true labels are like [0,1,0,0,0,2,1....]. I have to cluster them in 200 clusters. I want each cluster ...
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1answer
4k views

Decision boundary plot for a perceptron

I am trying to plot the decision boundary of a perceptron algorithm and am really confused about a few things. My input instances are in the form [(x1,x2),target_Value], basically a 2-d input instance ...
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1answer
115 views

What is the origin of the term confusion matrix?

The confusion matrix is a fundamental term in machine learning. However, that name itself is a bit, well, confusing. I tried to trace its origin but I'm not sure I'm correct, and I'd like to hear what ...
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1answer
159 views

What distribution is the expectation taken over in the total expected pay-off in reinforcement learning? Is it consistent with Bellman's Equation?

I was following the reinforcement learning lecture notes on CS229: http://cs229.stanford.edu/notes/cs229-notes12.pdf on page 3 they have the equation for the expectation of the total pay-off: $$ ...
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30 views

How do I get initial transition matrix probabilities?

I have to develop a system to detect and prevent bank transactions fraud - just credit card transactions, for simplicity - I'm thinking about using markov chain. How would I get the initial ...
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1answer
200 views

The meaning of the output from grid.py in libsvm

I'm a newbie in SVM, and have several questions regarding a tool in libsvm. There's tools/grid.py which tools/README explains as "parameter selection tool for C-SVM classification using 47 the RBF ...
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9 views

Sequence analysis with multiple sequences

I would like to recognize different states in a sequence of multiple vectors. To make it little more clear, here is an example: I have 2 (or more) vectors in a sequence: head position(HP) and eye ...
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0answers
37 views

Which machine learning technique is appropriate for my problem?

I'm new in machine learning topics and I've problem in modeling my environment which has multi parameters with different value ranges and a few actions to perform when value of each parameter is not ...
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3answers
56 views

Why do we do hypothesis testing on estimates of linear regression?

I was reading about linear regression and what I understood is that once we minimize OLS equation we get the beta parameters. Its just like solving a normal equation to get the unknowns. Then why do ...
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0answers
12 views

Calculate state change probability

I am having telco order management data and need to calculate the probability of each order going through different stages. data is like this: Order No; product_type; time spent in step1; time ...
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1answer
207 views

How to stack a convolutional autoencoder?

I am trying to figure out as to how to stack a convolutional autoencoder (CAE)? Consider a convolutional autoencoder (CAE) (using MNIST data, 28x28 input dimensions): ...
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1answer
261 views

Time series with multiple subjects and multiple variables in R

I'm having trouble finding a time series technique to deal with a data set I am working on. It contains multiple subjects and multiple variables, not all of which will likely be part of the time ...
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1answer
87 views

Machine learning on dummy variables

I have a dataset on which there are about 1000 dummy variables indicating location. I do not have access to lat/long. I am using xgboost to train it. The more that I train it does seem to be lowering ...
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18 views

Relation between precision, recall and sample size

I have a large data set for binary classification problem. Now in order to fit model to data I have been trying modeling using various sample size. For each sample size I gets a different precision ...
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10 views

SMOTE algorithm how to select over and under percentage?

I have a highly unbalanced binary dependent variable (i.e. cases of '1' is <5%). I am trying to implement SMOTE algorithm using R DMwR package. I wonder in general, how we determine the parameters ...
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1answer
198 views

Bernoulli mixture models for image classification, pathological cases

I'm trying to use a Bernoulli mixture model to classify MNIST images, and I'm running into pathological cases which screw up my calculations. The pdf of a multidimensional (let's say N dimensions) ...
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0answers
35 views

Confused Scikit results

I am doing classification machine learning on a particular dataset on which an SVM model (using Scikit.learn) is giving a Matthew's correlation coefficient (MCC) of ...
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0answers
16 views

Suggestions for Neural Network Structure for Time-Series prediction with constant covariates

I've been working on a time series prediction problem and wondered if someone has run across a similar problem structure & can make a suggestion on how to structure the training data, network, or ...
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0answers
27 views

How to correctly build a training/validation/test?

I have a database that is comprised of 3 sets of data. The first created in office conditions, the second in the same office taken on different day and the third drawn from random images from the ...
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0answers
12 views

How to do multi-labelling regression in machine learning?

There are a few links available to do multi-label classification (not to be confused with multi-class). But how to do multi-label regression given a highly non-linear real-valued data set? My ...
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0answers
8 views

Feature scaling when using Rectified Linear Units [duplicate]

Is it necessary to scale the input data of a Neural Network to a certain range (e.g. 0 to a big number) if the activation function consists of ReLus?
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1answer
28 views

Need guidance on image classification problem with large feature matrix

So I've got an interesting problem that I'm struggling with and I wanted to hear some ideas on possible solutions. The data is not public and I can't go into much detail. The problem involves a ...
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0answers
22 views

Normalization after PCA Whitening (for Deep Learning)

When training a Deep Learning model like an auto-encoder, is it necessary to normalize data again after it has been processed by PCA Whitening? Right now I zero-mean my data before PCA and use the ...
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2answers
32 views

How to calculate distance between points in DBSCAN matrix data?

I'm making a simple C implementation of DBSCAN following his pseudocode. If I well underand how DBSCAN works, I may represent my set of N elements (each with M features) with a NxM matrix. When it ...
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0answers
20 views

Converting between different accuracy/error metrics

I am trying to compare model accuracy between several different measurement metrics. For example, some citations use accuracy while other use error. That one is rather obvious, but there are lots of ...
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3answers
34 views

Backpropagation: Is there a general weight update rule for both output and hidden layers?

I'm looking for a general weight update rule for both hidden and output layers, no matter the number of layers, the connections or the transfer function. Does anything like this exist? I'm quite new ...
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0answers
25 views

Terminology clarification: Discrete distribution == Categorical distribution?

I'm reading "The Indian Buffet Process: An Introduction and Review" by Griffiths and Ghahramani and wanted to confirm my understanding of one of the terms they use. On page 1188, they say that the ...
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0answers
17 views

How do I reduce number of features without rebuilding the model?

I'm pretty new to ML/NLP thus my question maybe naive. How do I reduce number of features without rebuilding the model for Naive Bayes Classification? I'm using MALLET to build the model to classify ...