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

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Anomaly detection of web browsing sequences

Please consider that I'm quite new to machine learning. I need to create models based on browsing patterns of web users and find deviations from that model. I'm using web server access log files. For ...
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16 views

Basic idea of zero inflated two part models(hurdel) and application to big data (machine learning)

I'm currently working on the data which has 90% 0s in response variable. Based on my research, it seems zero inflated models could be a solution to this. However, while I was reading related ...
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10 views

Comparing learning algorithms

I know that you can compare learning algorithms based on their average cross-validation accuracy (e.g 10-fold, 10-repeated CV) and their test set accuracy. Suppose model 1 is a logistic regression ...
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9 views

Can network inference algorithms such as ARACNE handle time series data and how will they process it?

Simply put, can algorithms such as ARACNE handle time series data and how will they process it? For instance, ARACNE allows the user to input multiple columns of data and it considers each column an ...
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28 views

Algorithm for online handwriting recognition

Is there any specific algorithm for online handwriting recognition? The algorithm should recognize non-cursive and cursive handwriting. I know there is already a similar post on stackoverflow.com, ...
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11 views

How to understand kernel functions and how to choose a suitable kernel?

I am trying to describe my understand of kernels in the Support Vector Machine(SVM) and why some of them are more popular, but I am not sure if I misunderstand these concepts: 1) There are a large ...
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5 views

MDP value iteration

In Markov decision processes, what is the guarantee that value iteration chooses the same policy action from a given state for every iteration? I am referring to the slides given by AWM at ...
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17 views

Statistical Methods for Calculating Vending Machine Refill

Am looking into statics to help support a project I am undertaking. The project scope concerns intelligent replenishment / refill of vending machines. During an onsite service, a technician must ...
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2answers
54 views

ROC vs. Accuracy [duplicate]

If you want to compare two learning algorithms, which metric is better to use in general: ROC or accuracy? I understand that in ROC, you get both the sensitivity and specificity?
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Abnormalities in results L-LDA

For my research I am using Labelled Latent Dirichlet Allocation (L-LDA) on Reuters-21578 ModApte split dataset. In this dataset the news stories have a title and a body. To test the effect of L-LDA, I ...
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1answer
28 views

How do you measure the accuracy of an inference hypothesis/procedure?

Take inference to mean reasoning/predicting the value of a hidden/laten variable $Z$ given some evidence/data $X$. For example, maybe you are trying to find out if your patient has Cancer (Z = 1 if he ...
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1answer
15 views

How to apply properly k-nn algorithm when having several attributes

Let assume I have a dataset like this dataset where there are several textual attributes even continuos attributes like age. I have always encountered cases where k-nn is applied on just two ...
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2answers
87 views

About cross-validation for machine learning

Assume I have 1000 samples of data. I split the data randomly into training and test sets of size 800 and 200, respectively. Now, I train a classifier using the training set, and then evaluate the ...
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1answer
49 views

Does the vanishing gradient in RNNs present a problem?

One of the often cited issues in RNN training is the vanishing gradient problem [1,2,3,4]. However, I came across several papers by Anton Maximilian Schaefer, Steffen Udluft and Hans-Georg Zimmermann ...
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11 views

Propensity in linear models and bilinear regression models

I'm reading this paper about matrix factorization. In the paper they want to combine the features of the nodes in the model (page 6). First they illustrate the simple idea of combining the features of ...
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15 views

Intuition behind matrix factorization formulations?

I'm reading this paper about matrix factorization. In the paper they propose to use this factorization for the adjacency (or similarity) matrix $G$ using the following formulation: $G = U \Lambda U^T$ ...
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2answers
51 views

Assigning even partitions for Cross-Validation

This is a very basic question about cross-validation. Say that I have a sample size of 2901(or any difficult to divide number). How do I split this up into equal partitions (other than n=1)? And how ...
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1answer
29 views

One-class Classification of multidimensional vectors

I have a m x k User-feature matrix (m >> k) obtained by factorizing an original User-websites matrix (m x n) that has #page views as entries. Additionally, there are users (say r) who have been ...
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1answer
32 views

Is machine learning useful for comparing test group and control group

If you do a hypothesis to test the effectiveness of a treatment, or a marketing campaign, you want to be sure that the two groups are comparable. You can compare some relevant quantities between the ...
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1answer
23 views

Metrics for cluster evaluation

I make a set of clusters using some clustering algorithm. Precision, Recall, F Measure, Fallout and RI of individual clusters are calculated for testing the performance. How do I calculate the average ...
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1answer
36 views

Good machine learning algo for partial derivatives?

Does anyone know of good robust algos to estimate partial derivatives of a regression model? I am talking about a general regression model like this: $\mathbb{E}(y|x_1, x_2, ... x_n) = f(x_1, x_2, ...
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0answers
43 views

Training a Tic Tac Toe brain - am I on the right track?

My only experience with Machine Learning is Andrew Ng's Coursera course, but I did work through that just fine and passed with 100%. I decided to practice by making up some problems and solving them. ...
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1answer
19 views

Is Area under curve a composite function

I have some data examples. If I split the data into three parts and the have some scores for each example of the three parts and then calculate individual AUCs for the three parts In the next case, I ...
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2k views

What is the daily job routine of the machine learning scientist?

I'm a master CS student in a German university now writing my thesis. I will be done in two months I have to make the very hard decision if I should continue with a PhD or find a job in the industry. ...
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11 views

Updating SVD in Recommender Systems for change in ratings

I have read that there are projection based methods to accomodate for new user's ratings or for the ratings for a new item in SVD. However, I want to know how to update my feature space for change in ...
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9 views

how to implement linear or non linear regression for 3d position estimation?

I am a beginner in Machine Learning. For my project I need a regression algorithm that can estimate the 3D position of a device based on some constraints (moreover inputs). I know how to implement ...
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31 views

10 fold cross validation model in weka

Trying to build a specific Neural Network arcitecture and testing it using 10 fold cross validation of a dataset. Now building the model is a tedious job and Weka expects me to make it 10 times for ...
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15 views

Number of Predictors and Classification Algorithm

In general, is it better to include more predictors in algorithms such as SVMs and random forests compared to logistic regression? It seems that when we add more predictors to logistic regression, the ...
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1answer
51 views

For a model like this what performance measures can I calculate and how?

Methods: From the machine learning literature, I understand different parameters can show performance of model in machine learning. I would briefly expand my understanding with confusion matrix: ...
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1answer
17 views

Regression-tree Tuning in a Streaming Setting

Some time ago I went through a NIPS 2013 paper Regression-tree Tuning in a Streaming Setting. The paper proposes a tree-based regressor. Is there any implementation of this algorithm available? (At ...
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1answer
22 views

What do NORB and CIFAR stand for?

The MNIST dataset is a standard benchmark data set of digit images. MNIST stands for 'Mixed National Institute of Standards and Technology'. The NORB dataset is a commonly used dataset of binocular ...
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10 views

How to assess the importance of the features which come from intersection of features of the two models?

I have two models from two different data sets. Model 1 contain 50 features and model 2 contain 40 features. the intersection of features of model 1 and 2 is 10. so how can I assess the relative ...
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1answer
39 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 ...
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2answers
118 views

High precision with low recall SVM

I'm classifying a data set using SVM and those are the precision and recall values for two classes. ...
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19 views

Error in eval(expr, envir, enclos) : object 'Case' not found in train( method=rpart) in caret package of R [closed]

I am trying to fit my training data for Coursera Practical Machine Learning Quiz 2. ...
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1answer
21 views

SVM Classification with Duplicate Training Instances

I'm using SVMs with linear kernel for sentence classification (binary). My dataset contains many duplicate instances i.e. many sentences in the training set have identical feature vectors. In the ...
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1answer
15 views

How to compare the nested models which each of them comes from diffrent dataset?

I have four nested models.Every of them learned from different data sets. now I want to compare these models together.normally people try to compute the F-satistics. But for my case, it's bit harder, ...
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13 views

Difference between Factorization machines and Matrix Factorization?

I came across the term Factorization Machines in recommender systems. I know what Matrix Factorization is for recommender systems but never heard of Factorization Machines. So what's the difference?
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12 views

Expected required sample length to train a hidden Markov model

Say one wishes to train a hidden Markov model with $n$ hidden states, and (accidentally) the problem itself can be described with a hidden Markov model with $n$ (or less states). What is the expected ...
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1answer
27 views

k-means clustering on percentages

Can we do k-means clustering on percentage data (like 56%, 44%, 22%, 13%, etc.)? There is a data set, and data in various parts are measured in percentages.
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1answer
13 views

Assumption behind few latent features in recommender systems?

I know in recommender systems you have a rating matrix and then you factorize this matrix into two matrices and then learn those matrices with gradient descent. In those matrices we specify the number ...
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3answers
47 views

In Naive Bayes, why bother with Laplacian smoothing when we have unknown words in the test set?

I was reading over Naive Bayes Classification today. I read, under the heading of Parameter Estimation with add 1 smoothing: "Let $c$ refer to a class (such as Positive or Negative), and let $w$ ...
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1answer
62 views

How to decide which penalty measure to use ? any general guidelines or thumb rules out of textbook

A number of regularization measures are available in literatures, which is kind of confusing to beginners. The classical penalty is ridge by Hoerl & Kennard (1970,Technometrics 12, 55–67). ...
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1answer
65 views

How do you validate your machine learning models?

I am wondering what approaches are commonly used for validating a classification or prediction models: Approaches that am using at the moment: Using truth-sets: - ROCs, Bootstrapping, Accuracy, ...
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15 views

Forensics in wireless networks, anomaly detection and beyond?

first i'de like to apologize if this is not the right place. Next year i'm gonna be working on my final project in computer security, i have to build a wireless forensics tool that can analyse a data ...
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1answer
23 views

Feature Selection - Mutual Information with response variable that takes three values

I am trying to calculate Mutual Information scores for Feature Selection. I have successfully implemented the Mutual Information to test each feature against the binary response variable. Each ...
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1answer
30 views

Interpretation C value in linear SVM

My C value is very low (close to 0). Does this mean that my feature (dimensions) have no real separative (and thus predictive) value? (As the SVM basically chooses to ignore the training data ...
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1answer
52 views

Simple SVM Question

For a linear SVM, the documentation tells me the formula is: $$ \frac{1}{2}w^Tw+C\sum\limits_{i=1}^l\xi_i$$ Please explain to me in layman's terms what w (and ξ) represent. Is w the distance to the ...
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1answer
46 views

large variables and low sample (p > n) problem: ridge , LASSO, PLS, PCR which is most suitable for predictions

I am trying see whether to go for ridge regression, LASSO or principal component regression (PCR) or Partial Least Squares (PLS) in a situation where there are large number of variables / features (p) ...
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Should the 'TPR of adaboost' be better than base classifiers'?

There are two different base classifiers which produce true positive rate (TPR) values 99.46% and 91.79%. When I use these base classifiers in adaboost, what should the new TPR be? Better than two of ...