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

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Classification algorithms in R that accept training instances with weights

Are there any classification algorithms implementations in R such as Decision Trees, Naive Bayes, etc. in which the training instances can have a weight? I found this relevant question in ...
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2answers
97 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 ...
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1answer
28 views

Perceptrons and Decision Boundaries

I am currently studying neural networks and have been trying to reason about this for a while to no avail. I understand that given a perceptron(such as above) with f as a step function, any ...
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24 views

Correctness proof of bayesian networks

I want something simple and my brain is getting in my way. Assume I have three different coins - C1 is fair, C2 has p(Heads)=0.6 and C3 has P(haeds)=0.8 I want to draw a bayes network for the ...
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8 views

How to extract the feature and which ML method should be used

There will be seom bidding info. It need to tell which bidding is from which team. Or how other team will bid. The market will give the total demand every 0.5h. Then each team will offer their price ...
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20 views

package ‘imputation’ is not available (for R version 3.1.2) [on hold]

I am trrying to impute missing value by using impute function. But when I try ti install imputation package , I got this error: install.packages("imputation") Installing package into ...
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13 views

References for Evolutionary Computing and Quantum Computing [on hold]

Please give me some references for Evolutionary Computing and Quantum Computing. I am new in this topics. I am looking for elementary references so that I can understand this topics.
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7 views

SGD weight learning for mixture of generative models

Let's say that I've learned $k$ generative models $\mathbf{G}=G_i$ in some ways from my data. I'd like to create a mixture from them in order to have something like model averaging in this form: ...
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7 views

Pre-processing (center, scale, impute) among training sets (different forms) and the test set - what is a good approach?

I am currently working on a multi-class classification problem with a large training set. However, it has some specific characteristics, which induced me to experiment with it, resulting in few ...
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38 views

What type of ML algorithm do I need to use? [on hold]

I have a bunch of features of users, such as: age, sex, city and so on. And I have a system of split-testing. There are different experiments in this system and users are getting inside. There are ...
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1answer
31 views

What is the name of this validation procedure?

I have a set of classified data. In order to test the precision of several algorithms- I split the data into train and test sets. For the test set I choose at random 30% of the data and the rest is ...
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1answer
49 views

machine learning with linear regression algorithm

I'm noob in machine learning, but I'm trying to know more about it. I have a question about a prediction model (predict for every page when the number of click). I try to use kNNimpute to handle with ...
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8 views

Do class-conditional densities always have to sum to 1 conditional on the classes? [duplicate]

I read a lesson here: http://www.byclb.com/TR/Tutorials/neural_networks/ch4_1.htm, and noticed that the class-conditional densities did not sum to one (if we drew vertical lines in figure 4.1, the ...
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11 views

Prediction using categorical, binary and time series variables

I have per subject: categorical variables - ex: grade, mother_education continuous variables - ex: ...
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12 views

Hidden Markov Model vs Markov Transition Model vs State-Space Model…?

For my master's thesis, I am working on developing a statistical model for the transitions between different states, defined by serological status. For now, I won't give too many details into this ...
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9 views

Decision Tree English Rules and Dependency Network in MS SSAS

I created a Decision Tree model in Microsoft Analysis Services (SSAS, Visual Studio 2010). There are two tabs in the Mining Model Viewer tab: (1) Decision Tree that shows a tree itself, and (2) ...
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2answers
49 views

Precision, Recall, and PR Curve

I am doing research on binary classification. I have three classification models work on one data set. I have no True Positive, True Negative, False Positive, and False Negative metrics, each model ...
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1answer
30 views

How to measure co-adaptation occuring in a multi-layer perceptron neural network that does not use a drop out?

The dropout proposed by Hinton is said to prevent co-adaptation. My question is how can I measure the co-adaptation that occurs in a multi-layer perceptron that does not use a drop out?
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13 views

Weekly data normalization - Python

I have a weekly dataset and I have to normalize this data. Data is something like this : ...
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1answer
38 views

Is there any neural network whose output can be probabilistic, just like multi-class logistic regression?

I want to add nonlinear character into multi-class logistic regression. I know kernel logistic regression can do it. Is there any kind of neural network which has similar characteristic?
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9 views

Diagnostics for when data can't predict the Response [on hold]

Is there a way to diagnose that the data can not predict the response very well? I was given a task of classification a disease given some raw data. However no matter what I do the model, while the ...
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2answers
40 views

What is the proper name of a model that takes as input the output of another model?

Thanks in advance for the help. I am writing a paper and for the life of me can't remember the proper term for a model that works as follows. ...
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1answer
27 views

Questions about weather prediction in scikit learn

Hello I am a high school student doing research on weather. I have a dataset that has four columns each labeled with time, pressure, and lat/long. I am confused on the cross validation process. What ...
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1answer
40 views

How are individual trees added together in boosted regression tree?

I'm reading Introduction to Statistical Learning, James, G., et al. (2013), in which they describe the Boosted Regression Tree algorithm as following. What I do not understand is Eq 8.10 and 8.11. ...
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10 views

Using SVM Enron Spam Corpus for Advertising or Any spam Corpus [on hold]

This is a bit specific. I want to train a support vector machine or naive bayes classifier to spot advertisements in HTML so I can clean before LDA analysis. Only a few percentage points of bad data ...
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1answer
35 views

Problem with getting neural network learned to calculate XOR

I am learning about neural networks. I found a course on Coursera about machine learning https://www.coursera.org/course/ml . What I am trying to implement is a neural network to calculate logical ...
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16 views

How to do ranking with scikit-learn random forest model

I have a training dataset that I've developed, that has the following format: ------------------------------ | User ID | Item | Label | ------------------------------ | 001 | umbrella | 0 ...
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33 views

Can a Naive Bayes Model predict using pattern alone?

Say I have a set of data abc-def-ghi jkl-mno-pqr stu-vwx-yza and lots of other training samples which are catagorized as **names*. The above dataset does not have ...
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1answer
22 views

Is this a job for mixture of experts regression or semi-hidden markov models or something else?

Data I have several thousand timeseries each comprising around 365 data points. Browsing through a few of them, it looks like each timeseries consists of several regimes (different number f regimes ...
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19 views

Model selection and performance evaluation using cross-validation for time series with missing values

So my task is to select and evaluate a statistical model (random forest, boosted trees, neural networks etc.) for a time series with missing values around 10 years long. One of the goals of that is to ...
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9 views

Obtain Precision and Recall from Click through data

I am trying to build a graph of precision and recall using click data. I have two data sources. First data source has all the user clicked item_ids based on a given query_id. Second data source has ...
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8 views

Creating a model for a webshop

I'm going to create a Multi-armed bandit algorithm to handle recommendations for a large scale webshop. I'm going to use Thompson sampling (http://en.wikipedia.org/wiki/Thompson_sampling) and would ...
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1answer
49 views

Why can we assume that samples $X_i$'s are independent if the parameter is fixed (though unknown)?

To put it in context, I was trying to learn Bayesian parameter estimation (by an example of learning the probability of heads of a coin) and was trying to understand the independence of the samples ...
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44 views

What gradient descent method is better for convolutional neural network?

Let's say we want to train a convolutional neural network, what gradient descent method works better? (1) Batch gradient descend (2) stochastic gradient descent
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What is the difference between independent subspace analysis and independent component analysis?

What is the difference between independent subspace analysis (ISA) and independent component analysis (ICA)?
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75 views

Bayesian Linear Regression

I have the following question concerning Bayesian linear regression on my machine learning assignment: Consider $f = w^Tx$, where $p(w) ∼ N(w | 0, Σ)$. Show that $p(f | x)$ is Gaussian. I ...
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15 views

Formulating a classification problem as a Hidden Markov Model problem

I am told that this is a better place to ask for help on formulating a Hidden Markov Model: I am given a series of lines coming in one at a time. Each line contains 100 elements (basically gray scale ...
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1answer
9 views

What does ROC-EER in percent stand for?

Ive tried to understand what the ROC Curve represents and what EER (Equal Error Rate) means. And I somehow think I got to understand some of the explanations I read on the internet and videos I ...
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What is weakly-labeled data?

I am afraid I ask an easy question, but here are my questions: What is weakly-labeled data and is there any strongly-labeled data? In what situation do we use them?
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1answer
31 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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8 views

SIFT rotation invariance

In Scale-Invariant Feature Transform, keypoints in an image are extracted which are invariant to scale, rotation and translation. The keypoints contain information on the scale and gradient of a given ...
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22 views

Observed versus hidden variables for Bayesian network in this particular context

I am a novice in Bayesian networks. I have a problem which is best described (at least I think so) in the following story. One wants to predict earthquakes. Let's say it has 5 variables, the last one ...
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36 views

When to use K mean clustering and hierarchical clustering algorithm? [closed]

Can you please tell me when to use the K-mean clustering and hierarchical clustering algorithm and what is the different between them... Regards, Rahul
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3answers
79 views

Explanation on a Minsky's critique on statistical learning related to XOR

I was listening to the first session of society of Minds by Minsky (2011) and he mentions at some point around minute 48 the following: "...lots of statistical learning tools is good for lots of ...
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2answers
23 views

Inferring on an unknown number of function approximation

I want to ask whether a procedure to do the following job exists (or whether it makes sense for it to exist). First, assume we have $k$ functions $f_1,...f_k$ that have the same domain and range. ...
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30 views

Find distribution of Bus arrival time

I am currently working on a problem in my research which can be modeled into the following question: Let's say I have a rich dataset with values for the variable $A$ which is equal to ...
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16 views

Machine learning/random forests with noisy response data

Machine learning techniques like random forests seem to assume that the responses in the training set are known perfectly. Specifically for regression applications, it seems one needs to account for ...
0
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1answer
16 views

Viability of software dev - Use of and requirements of NN

Hello I would like to know this two things regarding the viability of producting a software, so: 1) Are available on internet some OCR libraries for free? Can I train my own NN having only a laptop? ...
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What is a good model for revenue managment / price optimization problem

I am trying to create a dynamic pricing model to optimize revenue for a hypothetical business. Lets say I have an application that connects dog walkers to people who want to pay for their dog to get ...
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1answer
29 views

make prediction with HMM

I want to use HMM to make some prediction. say $O$ is the observation, $S$ is the hidden states, and I know how to train the model with forward-backward algorithm. I just get confused with how to ...