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

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Classification on variable-length time series

I have a series of transactions like the following: [0, 2, 2, 3, 1, 0, 0, 0, 1] [1, 0, 0] [3, 3, 1, 1] I would like to classify each transaction as being part of one of two categories: class A or ...
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1answer
24 views

Maximum Likelihood Estimate (MLE) equivalent to finding $\hat y$ in linear regression with i.i.d. Gaussian noise distribution

In an assignment I need to show that for linear regression, with the noise i.i.d. Gaussian distributed $\epsilon_i \sim N(0,\sigma^2)$, that finding the Maximum Likelihood Estimate (MLE) is equivalent ...
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33 views

Are all models useless? Is any exact model possible — or useful?

This question has been festering in my mind for over a month. The February 2015 issue of Amstat News contains an article by Berkeley Professor Mark van der Laan that scolds people for using inexact ...
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17 views

Valid result when adding two kernels with negative coefficient?

If $k_1$ and $k_2$ be a kernel in $ \mathbb{R}^n \times \mathbb{R}^n $. we know $k(x,z)=ak_1(x,z) + bk_2(x,z)$ (kernel addition) is still a valid kernel if $\: a,b \geq 0\,$ ($a,b$ is real numbers, ...
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21 views

regularization in Machine learning [on hold]

Within the context of regression, we use regularization as a way to “control” the complexity of the hypothesis class; hence regularization introduces our own bias into the learning problem. True or ...
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93 views
+50

How we can calculate Fisher criterion weights?

I studying for Pattern Recognition and ML. I ran to one type of question: We define equal prior probability as: $P(D_1)=P(D_2)= \frac{1}{2}$ in two-class classification problem, if the ...
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2answers
70 views

Maximally reducing the rank of a matrix by removing some rows or columns

I have a $N \times M$ matrix, and the rank of matrix, $r$, is near $\min(M,N)$. I want to minimize the rank by removing some of the rows or columns to get $r \ll \min(M,N)$. The goal is to achieve ...
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117 views
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calculation threshold for minimum risk classifier?

Suppose Two Class $C_1$ and $C_2$ has an attribute $x$ and has distribution $ \cal{N} (0, 0.5)$ and $ \cal{N} (1, 0.5)$. if we have equal prior $P(C_1)=P(C_2)=0.5$ for following cost matrix: $L= ...
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17 views

Cross-Validation gives different result on the same data

I have done Cross-Validation by crossval function in matlab on my data, but when I run the Cross-Validation many times, it give me a different results, so is that ...
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3answers
750 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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2answers
65 views

Concept of p-vector and matrix

I have worked with vectors and matrices but the following paragraph from The Elements of Statistical Learning by Trevor Hastie et al is little confusing (online edition, page 10) Matrices are ...
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1answer
75 views

some inference about k-NN algorithms for better understanding? [on hold]

I ran into some facts make me confusing. for k-NN classifier: I) why classification accuracy is not better with large values of k. II) the decision boundary is not smoother with smaller ...
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1answer
79 views

Should you tune 'ntree' in the Random Forest algorithm?

In the original paper, I was under the impression that the RF couldn't really overfit. However, in practice I'm seeing that increasing 'ntree' sometimes increases test set error. Is this due to ...
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4answers
868 views

Introduction to machine learning for mathematicians

In some sense this is a crosspost of mine from math.stackexchange, and I have the feeling that this site might provide a broad audience. I am looking for a mathematical introduction to machine ...
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15 views

Clustering on this reinforcement learning approach?

I am trying to create an agent that selects an action depending on a state that gives back maximum reward. To keep things simple I will keep it to two actions and 24 different states. The states is ...
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1answer
236 views

Comparison of two classifiers based on precision/recall/F1 only?

For two classifiers h1 and h2 I have the precision, recall and F1 score as a percentage (along with the original labeled data set that they were tested on). If I had access to which samples each ...
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0answers
32 views

two margin comparison and one conclusion?

I read following notes, and couldn't get it. any idea or hint would highly appreciated. a SVM classifier using a second order polynomial kernel. The first polynomial kernel maps each input data x to ...
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59 views
+100

Learning user behavior that changes over time

I am learning a model using SVM that will predict user behavior of some kind. Simplifying this model, each example in the feature space contains some features: $f_1,f_2,..,f_n$ and a class $a$ that ...
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1answer
149 views

How to set the radius value in self organizing map?

I'm training the self organizig map, I need to set the value for the radius of it. is there any method to find the optimum radius size ?
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1answer
174 views
+50

Compute the probability that the provided classifier label is correct

A binary SVM classifier provides a label $y_c^{(i)}$ for each $i$-th sample provided. This is not assured to be corresponding to its true label $y^{(i)}$, since the classifier could have computed a ...
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1answer
123 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
21 views

variance in test accuracy will increase as we increase the number of test examples؟

I see this statement on 1 that say a True statement on Machine Learning Context. The variance in test accuracy will increase as we increase the number of test examples. my challenge is why ...
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1answer
13 views

1) State 2) Action and then 3) Reward diagram: Which ML approach to use?

It is looks like a reinforcement learning diagram however it's slightly different. I'll explain the numbers. 1) The environment first gives the agent a state 2) The agent does it's magic and then ...
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27 views

Supervised learning, unsupervised learning and reinforcement learning: Workflow basics

Supervised learning 1) A human builds a classifier based on input and output data 2) That classifier is trained with a training set of data 3) That classifier is tested with a test set of data 4) ...
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3answers
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Semi-supervised learning, active learning and deep learning for classification

Final edit with all resources updated: For a project, I am applying machine learning algorithms for classification. Challenge: Quite limited labeled data and much more unlabeled data. Goals: ...
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16 views

Which machine learning(recurrent/reinforcement learning) method/algorthim would suite this scenario

This application has it's roots in public transport, users opening the application and looking at the departure times of buses for specific stops (page 1) or planning a journey from location A to B ...
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2answers
234 views

Heuristic Feature Selection for Gradient Boosting

I originally posted on Stack Overflow and was told to move it here. If I am trying to select from two different sets of features for a Gradient Boosting Machine, but I do not want to run through ...
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1answer
32 views

What is the “standard reference” for cascade forward neural network?

What is the "standard reference" that firstly describes or surveys in details the cascade forward neural network? This kind of net is available in matlab toolbox for long cascadeforwardnet (as early ...
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18 views

Are there shape-matching scores that take into account multiple scales simultaneously?

Say you are determining how well your model of an object matches an image. To score this match, we can use e.g., the cross-correlation coefficient (CCC), giving an overall shape match. This works for ...
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1answer
72 views

How to standardize text data for training Neural Networks?

I want to train neural network with text data(natural language) as input for classification purpose. One way for standardizing text data for neural network is to use N-GRAM/SKIP-GRAM representation ...
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82 views

How many features will be selected by mutual information and wrapper in information filtering?

I see one example in old-mid exam from well-known person Tom Mitchell, as follows: Consider learning a classifier in a situation with 1000 features total. 50 ...
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15 views

linear discriminative analysis for regression

LDA computes a projection matrix to maximize class conditional probability. Similar to this, is there any exisiting method or library for jointly learning latent space and minimizing the regression ...
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9 views

EM to Variational EM in LDA

Why exactly, when learning hidden variables distribution in LDA(Latent Dirichlet Allocation), one cannot use to the EM (Expectation Maximization) algorithm and have to resort to a variationnal EM ...
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114 views

Binary classifier probability measure?

I've the following situation. I've a binary classifier which classifies input feature vectors into either of two classes '$y$' or '$n$', along with the probability of it being in either of the ...
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2answers
143 views

Predict interesting articles: increase accuracy

I'm trying to write a GUI to display articles, and predict which articles I could like, based on the articles I previously liked. This post is the continuation of this one: ...
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1answer
13 views

What is the difference between linear perceptron regression and LS linear regression?

Recently, a project I'm involved in made use of a linear perceptron for multiple (21 predictor) regression. It used stochastic GD. How is this different from OLS linear regression?
2
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1answer
93 views

Detecting strong currents in a sparse directed graph

I have a very large, sparse, weighted, directed graph. The structure is such that it mainly consists of strings of nodes connected with highly weighted edges. These strings can be connected by weak ...
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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 ...
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2answers
147 views

Class labels in data partitions

Suppose that one partitions the data to training/validation/test sets for further application of some classification algorithm, and it happens that training set doesn't contain all class labels that ...
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14 views

Matching a query distribution to a family of template distributions

I was turning over a hypothetical question in my head: Suppose I have a set of template probability distributions, let's say each giving the probability of the occurrence of certain objects like ...
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2answers
151 views

Anomaly detection with a multivariate Gaussian vs. PCA + univariate Gaussians

In Andrew Ng's Machine Learning Coursera Class, he covers anomaly detection in multiple dimensions for both independent univariate Gaussians and multivariate Gaussians, the latter being more costly ...
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1answer
37 views

a challenge with linear classification and distance to origin? [on hold]

I ran into a problem, when studying on linear classification. my prof. says: in a linear classification $y=w_0+w_1x_1+w_2x_2$ that depicted on following figure, distance of origin to decision ...
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21 views

What is the commonly used mehtod for measuring variance of accuracy mean using k-fold cross validation?

I know there are planty of questions about standard deviation, though I didn't find an answer tuned to my particular need and also I could really use your help! I'm performing 18-Fold Cross ...
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1answer
72 views

random forest modelling with high dimensional data

I am puzzling on developing random forest regression of high dimensional data. My predicted variable is plant cultivar or Class (say 1, 2, 3) and regresser are 82 variable in separate column (40 X 83) ...
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2answers
118 views

Instance weighing in libsvm/liblinear

I often use the instance weights with Libsvm for classification problems. http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/#weights_for_data_instances Does anyone know the details of the algorithm that ...
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9 views

How to create and format an image dataset from scratch for machine learning?

I've only worked with ML with .csv formats. I've worked with image formats too but only premade imagesets (MNIST,etc). If I were to create an imageset from scratch, how are the class labels typically ...
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12 views

graph classification task - multi label?

I have a data set in graph format representing semantic connection between terms. The data set is divided into clusters, each with several labels (not unique, or mutually exclusive, no set number of ...
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2answers
311 views

Times series analysis vs. machine learning?

Just a general question. If you have time series data, when is it better to use time series techniques (aka, ARCH, GARCH, etc) over machine/statistical learning techniques (KNN, regression)? If there ...
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Learning from streams with concept drift in real world - how to handle missing class problem?

In currently delves into learning from streams with concept drift. As more I learn I think about how I can use learning algorithms on real data. Most of drift detection algoritms to evaluate is ...