Questions tagged [probability]

Probability is the branch of mathematics concerning numerical descriptions of how likely an event is to occur or how likely it is that a proposition is true.

Filter by
Sorted by
Tagged with
0
votes
2answers
1k views

What are the inputs to a logistic regression? Probability or trial result?

It is a very basic question, but cannot find a satisfactory answer to. When we do logistic regression, what are the inputs? Suppose we have a dataset of students giving number of hours each student ...
0
votes
2answers
192 views

Logistic regression prediction changed after executed couple of time

I noticed that after each time I execute the following lines of code, my results are different. Any idea why? I think that the main issue here is this line of code But I dont understand why? ...
1
vote
1answer
197 views

Softmax function forms

The constraint that the n outputs must sum to $1$ means that only $n−1$ parameters are necessary; the probability of the $n^{th}$ value may be obtained by subtracting the first $n−1$ probabilities ...
1
vote
0answers
70 views

Training HMMs using the EM algorithm

How would I train an HMM using the EM algorithm so the transition matrix is upper diagonal?
-1
votes
1answer
47 views

Determining Statistically Significant Differences in Views per Day of Week?

I have some views per day of week data. It's something like: Mondays: 100k views Tuesday: 110k views Wednesday: 140k views ... Sunday: 80k views So naively, it seems like Wednesday is a better ...
2
votes
1answer
331 views

intuition behind the difference between likelihood function of discriminative and generative algorithms

I am currently studying the online material of Stanford CS229 and I came across the likelihood function for discriminative(for example, regression) and generative algorithms(for example, naive bayes): ...
2
votes
1answer
805 views

Question Regarding Multi-label probability predictions

I have been doing a problem in which I have to predict probabilities for each of the labels in a multi-label (four to be precise) classification problem. Example of a solution: ...
0
votes
1answer
252 views

Propensity Modeling, still use Test/Train Split?

I'm using Sklearn to build a classifier in which my client wants a predicted probability for each row of data. The default of let's say Random Forest is if > 50%, then classifies as TRUE, but using ...
2
votes
2answers
721 views

Linear Model to generate probability of each possible output

This is related to Sports prediction (Cricket). I am new to Machine Learning and learning it through TensorFlow. I am focusing only on one topic which is "How many runs ...
5
votes
2answers
3k views

Confidence intervals for binary classification probabilities

When evaluating a trained binary classification model we often evaluate the misclassification rates, precision-recall, and AUC. However, one useful feature of classification algorithms are the ...
1
vote
1answer
257 views

How to estimate the transition probabilities for a Markov Chain when time intervals are non-equally spaced

I've been given a dataset with a number of observable states. I am trying to apply a Finite State Markov Chain to model the system, but I found that I can't estimate the transition probabilities if ...
0
votes
1answer
307 views

Why predicted proababilities from this binary classifier does not sum up to 1?

I have a C5.0 model that is trained to predict binary class (C1/C2) on a dataset with 20 features. The model is configured to perform boosting (10 trials) and it has a ...
-1
votes
1answer
475 views

Probability of what product will be purchased in repeat orders

I have a problem I need to solve and am looking for assistance in what algorithm to use. I have a online store that I have say 10 products and I have all the order history for every order. What I am ...
-1
votes
1answer
589 views

how to find / rank the most explanatory variables of a regression

Let's say I have m training examples with n continuous explanatory variables x1, x2,..., xn and a label y. I'm doing a linear regression. Is there a way to rank what combinations of explanatory ...
2
votes
2answers
159 views

Modeling the influence of events order on probability

The case is to model if the sequence of events influences the probability of binary target variable. We have for example five different events which occur in time (event: A,B,C,D,E). They can occur in ...
1
vote
0answers
81 views

Hidden Markov Models: Linking states to labels after EM training

The tl;dr version first: I have the following problem: I implemented Baum Welch for ergodic HMMs. I do it like this: I pass the model two number C1 and ...
2
votes
2answers
137 views

Proceeding with various methods for news recommendation

I am beginner in ML (i have done only Andrew Ng's ML course) and i have to work on news recommendation. I went through this paper which mentions different methods used for news recommendation (at 7th ...
1
vote
0answers
19 views

Antisymmetry of graph of Information vs probability

The formula for Information given by a data of occurring with probability p is: I=-log2 p This formula gives the bits if information needed to know the outcome of the event. This formula captures ...
1
vote
0answers
751 views

Generalization error for simple linear regression

Lets say we have a training data and we have estimated a fit for a model of square ft of living area vs price of houses. Suppose we know the probability distribution of sq ft and for a fixed sq ft we ...
2
votes
1answer
490 views

Classification problem approach with Python

I am a Python beginner, just getting into machine learning and need advice on the approach i should use for my problem. Here is an example of my data-set. Where the RESULT is a corresponding INDEX ...
1
vote
1answer
614 views

What is the procedure to create a bag of visual words model with SIFT?

I have more than 1500 black and white classified images in a training set and I want to create a probabilistic model to classified new images. To be more explicit, given a new black and white image, ...
2
votes
1answer
8k views

What is “noise” in observed data?

I am reading pattern Recognition and machine learning by Bishop and in the chapter about probability, "noise in the observed data" is mentioned many times. I have read on the internet that noise ...
0
votes
2answers
579 views

How do I calculate the maximum likelihood (machine learning statistics) of this table of data?

I’m taking a machine learning course and I’m stuck. I've already tried to ask around in the forums of the class but I don't understand how to implement the formulas they give me. Can you please help ...
0
votes
1answer
161 views

Multilabel Classification - increasing the confidence

I have a basic multilabel topic classifier(Tfidf vectorizer with OneVsRest Classifier) built on some customer reviews. I observed that there are some classes with right features but it still predicts ...
2
votes
0answers
476 views

Implement gaussian mixture model with stochastic variational inference

I am trying to implement Gaussian Mixture model with stochastic variational inference, following this paper. This is the pgm of Gaussian Mixture. According to the paper, the full algorithm of ...
0
votes
1answer
119 views

Is there any other probability distribution model than gaussian for multivariate data

Whenever we talk about the probability distribution of data having more than one feature, we have only one option i-e multivariate normal distribution. Is there any other probability distribution ...
2
votes
3answers
475 views

In supervised learning, what does “Estimating $p(y \vert x)$” mean?

I read chapter 5.1.3 of Joshua Bengio's deeplearning book, which says: supervised learning involve observing examples of random vectors $\textbf{x}$ and associated value or vector $\textbf{y}$ and ...
2
votes
0answers
37 views

Is there a counting sketch optimized for intersections?

Popular counting sketches(loglog, hyperloglog, etc) feature natural union operations. Are there any known counting sketches that feature natural intersection operations?
5
votes
2answers
12k views

Xgboost predict probabilities

When using the python / sklearn API of xgboost are the probabilities obtained via the predict_proba method "real probabilities" or do I have to use ...
3
votes
1answer
930 views

Selecting the right algorithm for match probability prediction

Looking for assistance kick-starting a new machine learning scenario. In this case I need to pair one entity (ex. person) with a group of entities (ex. other people) given a history of matching ...
0
votes
2answers
131 views

Which features can help to differentiate these two density?

I'm wondering that is there any features that can help in differentiating the following two images. I mean differentiating in related numbers.
4
votes
1answer
156 views

which loss function (if any) optimizes the calibration graph

The calibration graph is the predicted versus actual probability(see http://scikit-learn.org/stable/modules/generated/sklearn.calibration.calibration_curve.html). Is it possible to optimize the ...
-1
votes
1answer
131 views

Topic modelling or simple case of calculating probabilities?

I am trying to find the common topics between articles read using the respective tags attached to each article. Background of my mini project: The problem I am trying to solve involves looking at ...
2
votes
1answer
113 views

How to determine individual contribution when data is aggregated by team

I want to know the individual contribution of each salesperson in terms of actual sales where the dataset I have aggregates sales data by sales "team". The dataset looks as follows: ...
0
votes
1answer
321 views

Estimating expected revenue generation

I have a number of features X and a target which is the revenue generated by this interaction. More often than not no revenue is generated, but if there is it can differ considerably, it has a big ...
2
votes
1answer
1k views

predicting probability distribution for time series

I have time series of several variables. Just in one specific case one variable is linear combination of the rest. I want to predict probability distribution (that is not only best estimate but ...
2
votes
1answer
57 views

Equation for likelihood in logistic regression

I read the likelihood is defined in logistic regression as the probability $$ L(w) = P(y|x, w) = \prod P(y^i| x^i,w) = \prod (\sigma(z^i))^{y^i}(1-\sigma(z^i))^{(1-y^i)} $$ and the log of the last ...
3
votes
1answer
2k views

What is difference between Bayesian Networks and Belief Networks?

While reading some articles about Bayesian Networks, I came across many occurrences of Belief Networks. Do both of these terms mean the same thing or is there any difference between Bayesian Networks ...
2
votes
2answers
3k views

Are real analysis and measure theory essential to learn for data science? [closed]

Some people say data scientists don't necessarily need to know real analysis and measure theory, but for others, real analysis and measure theory are very important for the undersdanding of kernel ...
3
votes
5answers
1k views

How to predict the probability of an event?

I have a dataset where a set of people donated for charity along with the dates of the donation. I have to find the probability of each donor donating in the next three months. Data is available from ...
1
vote
0answers
528 views

Score probability groups with Random Forest in R

I would like to use RF in order to get a score probability of a binary outcome, in order to know groups with higher probability of buy something. Like this: ...
1
vote
2answers
998 views

What is the appropriate evaluation metric for RandomForest with probability in R?

In order to build a predict model with two categories (buy or not buy),I want to use RandomForest and predict with type='prob', so I can have a prob of someone buy or not buy. So, with this outcome I ...
0
votes
1answer
126 views

crow probability problem [closed]

I am trying to solve the following problem, but am having some difficulty. Can anyone give me some guidance? There are lots of tourists in Grandeville. The streets in Grandeville run east to west ...

1 2 3 4
5