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

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32 views

Feature selection: PCA vs intuition? [closed]

Which one should I choose? How can I combine them (i.e. in series or parallel)? What if there are dummy features in my data? What if my intuition messes things up?
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1answer
14 views

Loss function/error measurement for allocation problem

I'm working on a prediction rule for an allocation problem. So, it's data like this: ...
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23 views

can I use the cluster membership from cluster analysis for future prediction (classification)

We had a survey of >1500 patients, and we did cluster analysis, and grouped them into 3 clusters. We want to develop a algorithm to predict cluster membership of future patients. But the question is: ...
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1answer
26 views

Is K-Means used the right way?

I have this model where I have a count of a word. Every day I do a count of the word and then calculate a simple ratio for this word by saying: ...
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15 views

More than one output neuron firing [closed]

I am building a neural network to solve a multi-class classification problem. Is it possible for more than one output neuron to fire?
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35 views

Learning from clicks on Ads [closed]

I need to build an algorithm that predicts the number of clicks a facebook ad would get in the next 7 days. Based on the given requirements, I prepared a dataset consisting of the following ...
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13 views

How to obtain a confidence interval or a measure of prediction dispersion when using xgboost for classification?

How to obtain a confidence interval or a measure of prediction dispersion when using xgboost for classification? So for example, if xgboost predicts a probability of an event is 0.9, how can the ...
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7 views

RBM with float units in visible layer

Currently I have been studying RBMs and concluded that it could be good model for my purpose. In my case Visible layer should be real valued of both signs, basically it is just word2vec values (which ...
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0answers
22 views

What exactly is the mathematical definition of a classifier / classification algorithm?

I just started an intro machine learning course, and to get things better organized in my head, I was trying to come up with exactly what is needed to completely specify a classification algorithm. I ...
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20 views

Which ML Algorithm for predicting starting parameters?

I'm experienced programmer but have never been in contact with serious machine learning. I want to know if there is a good algorithm/approach to a problem I have: I am optimizing a large number of ...
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16 views

Preparing the data for neural network

I have 2 categorical variables Make and Model as inputs. I am trying to imagine how the data will look like. I am going to pass a training example through the network that is a vector that gives a 1 ...
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2answers
78 views

In gradient descent, how can a function with higher cost better fit data than a lower cost one?

Based on the Coursera Course on Machine Learning, I implemented batch gradient descent using python. The progression of $J(\theta)$ is expectedly decreasing (which suggests that my implementation is ...
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36 views

How would Y-aware PCA for binaries look?

I recently stumbled upon Y-aware PCA in the blog of win-vector. They describe how PCA can be adjusted not to explain variation in $X$ but covariation of $X$ and $Y$. This is explained for the case ...
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28 views

What is the problem with negative eigenvalue (in gram-matrix) in SVM?

This is probably very basic, but I still don't know the answer. I am working on homework in my course, and one of the questions is dealing with negative eigenvalue in gram matrix at SVM, can someone ...
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18 views

what machine-learning model best fits 'tennis-like' scoring model

I have access to live data for some game. a team gains a point and the game is reset. the game ends at some threshold of points. My goal is to predict which team will win. I would be using the ...
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25 views

Are Residual Networks related to Gradient Boosting?

Recently, we saw the emergence of the Residual Neural Net, wherein, each layer consists of a computational module $c_i$ and a shortcut connection that preserves the input to the layer such as the ...
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1answer
56 views

Neural Networks Vs Structural Equation Modeling What's the Difference?

I'm studying about artificial neural networks (ANN) for the first time and I am struck by how the concepts of neural networks appear to be similar to structural equation modeling (SEM). For example, ...
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40 views

Why should I choose features or plot them manually when there are built-in functions to do that?

Why should I select variables due to my intuition if there are builtin functions in sklearn python like SelectKBest() and PCA() If I plot graphs of features of the data to see if they can detect the ...
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1answer
19 views

How to know if my Gaussian mixture model has enough training data?

A somewhat soft question - I'm training a Gaussian mixture model (with the EM algorithm) on data of size $N$ ($N$ is typically between 4 and 64). How much samples do I need? obviously it depends on ...
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1answer
33 views

Are the distances of the kNN i.i.d?

Imagine the set of i.i.d observations $D = \{x_i\}_{i=1}^N \subset X^n$. Let the distance function $d \colon X^n \times X^n \rightarrow \mathbb{R}$ be used to find the $k$ nearest neighbors to the ...
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2answers
20 views

comparing set sizes of algorithms that explain strings from a blackbox algorithm

Let's say that i have a blackbox algorithm that takes no parameters, does not halt, and produces values at some rate. Now then, let's say that over 10000 values, the string always follows symbol 'A' ...
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2answers
25 views

Which of the 3 cases should my data matrix belong to ideally?

I found this question, and while useful, I wanted to ask something more spcific: I am trying to get a good handle/intuition for the two types of data dimensionalities (number of data samples, and the ...
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15 views

Example usage (in Python) of Kalman Filter as it pertains to BASKET trading

I've found plenty of examples in Python of the Kalman Filter as it pertains to PAIRS trading, but what I'm really interested in are examples of how it can be applied to BASKET trading. Without a ...
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0answers
32 views

Scaling the data in a decision tree changed my results?

I know that a decision tree doesn't get affected by scaling the data but when I scale the data within my decision tree it gives me a bad performance (bad recall, precision and accuracy) But when I ...
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30 views

which is the most sutible technique to detect outliers? [closed]

i know a technique to detect outliers: 1- make a model & calculate residual for each data point 2- delete the top 10% residuals from the data 3- fit the data again that's fine but this leads ...
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2answers
37 views

Is it possible to make the non-separable data more separable by any methods of feature selection, extraction or transformation?

Could these data (in the figure below) be separated by any means of feature extraction, transformation, or it's just a waste of time to make the three classes separable if they "in fact" weren't ...
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53 views

Hypothesis Testing and Machine Learning [closed]

I am trying to figure out which is the best machine learning algorithm to use to solve this problem: Let's say I have a table, with each row such as this: ...
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1answer
39 views

Scalable Random Forest For Massive Data

My problem is simple. I want to train a dataset using random forest on a huge dataset (with $n$ rows). Let's assume I can only fit $b < n$ rows in memory at a time. Model Choice I see several ...
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8 views

Time-varying predictive model for a set of proportions

Suppose there is a casino where people bet on a weekly horse race. On Sunday, the casino publishes the prices for a wager on each horse for the upcoming Saturday's race. Everyone who wagers on the ...
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1answer
24 views

How to make this data in the following figure separable for the classification into three classes?

The figure below shows the PCA projections of inputs which are 14 meteorological features, (i.e. wind, temperature, humidity, pressure, and so on.) I would like to use any technique to make it more ...
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1answer
17 views

How to deal with a variable-sized real vector of inputs?

I have a collection of objects with properties that I measure. For each object, I obtain a vector of real numbers describing that object. Each object results in a vector having a different length. I ...
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2answers
62 views

Best way to optimize MAPE

The MAPE is a metric that can be used for regression problems : $$\mbox{MAPE} = \frac{1}{n}\sum_{t=1}^n \left|\frac{A_t-F_t}{A_t}\right|$$ Where $A$ represents the actual value and $F$ the the ...
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1answer
28 views

What is the origin of the rule of thumb for the number of samples needed machine learning?

I've heard that as a rule of thumb, the number of samples needed for a machine learning algorithm to get accurate results is ten times the number of degrees of freedom. For example, classifying an 8x8 ...
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1answer
13 views

Outsource machine learning tasks while keeping information confidential

I have some raw data that I would like to transform into a dataset, then ask for external parties to help me build model (with criteria such as minimising log loss, maximising area under curve). If ...
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2answers
77 views

Fourier transform in Machine Learning

I want to know what are the specific areas in which Fourier methods are used in machine learning. Apart from feature extraction and spectral analysis, I want to know if there are any learning ...
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1answer
18 views

How do I eliminate the effect of one variable while doing local regression?

I have a time series of data, each corresponds to a time point, a dose and an expression level. Say the dose is increasing in a trend like 10, 10, 20, 20, 20, 30, 30, 30, 30, 30, 40. Now I want to do ...
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0answers
13 views

Non-GLM Models in R for Fractional Response Variable

I am searching for a machine learning algorithm that I can use to predict customer retention/churn rate. My response variable is a proportion in the range 0 to 1 (0 and 1 inclusive). I am using R. The ...
2
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1answer
29 views

SVM cost function: old and new definitions

I am trying to reconcile different definitions of the soft-margin SVM cost / loss function in primal form. There is a "max()" operator that I do not understand. I learned about SVM many years ago ...
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0answers
31 views

Dealing with noisy/mislabelled dataset

I have several datasets where each instance has numeric label assigned by a human that can take values between 1 and 5. After doing a manual inspection of one of these datasets, I noticed the ...
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21 views

Feature ranking for *known* clusters

I am aware of feature ranking (i.e. selecting the 'best' features) for a binary classification task based on some model, however, I was wondering how to do this in the absence of a model? For example, ...
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8 views

Architecture of Input layer for categorical variables

Suppose I have three categorical variables make, model, and year. I am trying to find how many neurons I should have in my input layer. Suppose Make contains three elements: Honda, BMW, and Mazda. ...
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1answer
33 views

10-fold cross validation on small number of examples

I have a set of 100 examples evaluated using 10-fold cross validation, providing 94% classification accuracy on the test folds. However, when I test the model on a different test set, it provides 0% ...
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0answers
17 views

Effect of feature normalisation w.r.t. another feature in machine learning tasks (Regression, classification)

Let's say we have a set of features, and in this set of features there is one which is highly correlated to the others. What would be the implication of normalising the other features with respect to ...
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16 views

How to relate distributions?

I have 100 objects. Each object has 10 (highly correlated) attributes that I can measure. For each object, I obtain 10000 samples of that object's attributes. I now want to relate the attributes ...
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1answer
57 views

logistic regression vs support vector machines

I can understand the logistic regression depends on entire data and support vector machines depend on support vectors, but could not understand when and why should I use svm or logistic regression. ...
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1answer
41 views

Creating a new PC variable based on PCA loadings

I am trying to find variables which would be good predictors for the "stool" variable in my data. I was thinking I would use PCA to create a new variable which accounted for most of the variance in ...
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0answers
19 views

calculate p-value for AFT survival model

I am using Spark ml library to do some survival analysis. Here is the documentation. After training an AFT survival model, I cannot get the p-value directly as in R. What is available for the model ...
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71 views

Can (loopy) belief propagation be used to learn from a data set?

I'm trying to expand my experience with restricted Boltzmann machines to a more general class of graphical models and currently learning about belief propagation using message passing algorithms. One ...
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1answer
27 views

How to find how which inputs correlate to output in XOR way

Let's say this is my function: bit f( bit bits[] ) = bits[0] ^ bits[2] ^ bits[7] ^ ... I have a list of bits[]. I ran the ...