# 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.

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### Probability Distributions

I was going thru a course on probability and probability distributions for data science and in that they were describing the various probability distributions with mathematical formulae. I was ...
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### Reinforcement Learning: Formally, does an exponentially decaying epsilon satisfy GLIE?

I am aware that exponentially decaying exploration constants (epsilon) are used practically. Formally, though, do they satisfy the GLIE condition? Specifically, relating this to the Borel-Cantelli ...
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### What does maximize average log probability mean?

In the word2vec paper (https://arxiv.org/pdf/1310.4546.pdf) that introduces the skip-gram algorithm we encounter this phrase: which says that we maximize the average log probability. Can someone help ...
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### Conditional density estimation for sequences using conditional random fields

I am looking to estimate the conditional distribution of the next observation $x_{t+1} \in \mathbb{R}_+$ of a discrete-time process, given the current observation and $l$ previous observations. I am ...
26 views

### Check the validity of the distribution in the proof of No-Free-Lunch Theorem

I'm reading the proof of No-Free-Lunch Theorem (quoted at the end of this question) in Understanding Machine Learning: From Theory to Algorithms, Cambridge University Press, p.37, the author wrote: ...
31 views

### Is probabilities mean of predicted class (RandomForest) a consistent estimator of class recall?

I'm working on a classification problem in order to predict among 50 different classes. I'm using a Random Forest classifier and I'm using the predict_proba method ...
143 views

### Hi, I need help with this question. This quesion is based on Markov Chains. I want to answer it without using any simulation

Alinah is spending the summer at her grandparents’ farm in a small town in Iowa. The town is known for frequent changes in its weather. Each day starts off as either sunny or rainy. There’s a 50% ...
1 vote
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### Intuition behind Jensen Shannon divergence between deep features of two images?

Jensen Shanon divergence is mainly used to determine the divergence between two probability distributions. Can it be used to calculate the difference between the deep feature vectors of two images? I ...
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### Looking for suggestions on how to distinguish between two different distributions in my data when no labels are available

My data consists of medical claims from thousands of providers across the country. The data contains how much they were paid for each service they performed and how many units of each service they ...
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### Understanding the calculations of bayesian classification rule given features with known distribution

I have some difficulties using the Bayes rule and the calculations used for estimation of a given class in a classification task if we know the distribution (and its parameters) of the feature vector: ...
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### Does the central limit theorem and confidence intervals apply to any distribution, including memoryless distributions?

Is it possible to assign a 1 or a 0 to values in any distribution, be it a memoryless power law or pareto distribution to match some criteria such as if a value is under 10 it gets a 1, otherwise it ...
33 views

### Common cross-validation code: why does it work?

The following Python code is common practice when creating a folds column for multi-label stratified k-fold cross-validation: ...
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### Do models of social systems suffer from prediction drift?

Background I've created a binary classification model that predicts the probability of fraud for a given sample. The choice of threshold allows me to set how many frauds are captured in the training ...
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### Problem formulation of future timeframe prediction based on current time

I have a problem where I want to predict "when is the next action happening" based on the time. Example problem: Imagine you have a dataset of transactions per user, your goal is to predict ...
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### Getting probability to finish in the last 3 ones after each game week

I'am working on a dataframe with five differents features : team game_week season cum_points : pre game cumulative number of points final_position Those datas are covering 10 seasons of Premier ...
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### Framing a probabilistic time dependent problem

I need help framing the following problem: I have a dataset where I know for each day, at customer level, that someone with device X bought device Y. Example: At day 1 50 people with device X bought ...
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### Probability of a Maximum in a Time Series Given Past Data

I'm trying to predict the peak power usage of an EV charging station. I would like figure out probability bounds given the peak power throughout the month. Imagine that our EV time series consists of ...
1 vote
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### Trying to extrapolate info from a partial data set - statistical inference

I am wondering if my logic is OK here or not. 98% of a group without a device has an event occur 2% of group with device has an event occur Since we know that correlation isn't causation I can't say ...
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### Kernel Density Estimation and performance evaluation

I am doing a data science project about Kernel Density Estimation, specifically about finding the best bandwidth and kernel function to use. I need to use data that I don't know the actual underlying ...
1 vote
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### probability distribution

Just wanted to know if the value we get by passing, say, random.normal(shape=(3,2)) in the Tensorflow, etc, are normally distributed or if they are randomly chosen ...
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### Precision vs probability

Say I have a model which predicts a class $C_i$ from an input $X$, with a probability of 0.95 i.e $P(C_i| X)=0.95$. That would mean that if we do this over and over, then 95/100 times we would be ...
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### Predicting probability of reaching a milestone -- How much data should I use from production universe to train/test model?

If I am predicting probability of a business to reach (x) milestone (classification 1), but the only data I have is live production data, how much of the production data should I use to train the ...
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### Evaluating models which classify on rolling time intervals

TLDR: I am trying to predict the probability of an incident occurring within a specific time interval. I have data from multiple years, and I know the exact time of year that incidents occur. I have ...
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### Get dependant probabilities in multiclassification

After training my CatBoostClassifier model I call get_proba function which returns me list of probabilities. The problem starts from an another point... I transfer that data into dataframe then to ...
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### What does it mean to "condition' a net's output?

Graves talks about conditioning the predictions of a net based on inputs. What does that mean, and how is it done?
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### How to demonstrate two variables are orthogonal with respect to the output in a 3-D Python dataset?

I have a Python dataset with 300 samples and 3 columns: 2 independent integer variables X,Y and the dependent continuous variable ...
1 vote
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### Calculationg perplexity (in natural language processing) manually

I am trying to understand Perplexity within Natural Language Processing as a metric more fully. And I am doing so by creating manual examples to understand all the component parts. Is the following ...
1 vote