Questions tagged [prediction]

For questions about prediction of a certain quantitative or a qualitative value by an algorithm

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What model can solve vector to vector prediction?

I am totally newbie into serial prediction. I am think about which model or AI paradigm can be used to do vector to vector prediction? For instance, [1,0,1] ^ [0,1,0] = [1,1,1] Another example could ...
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Is there any way to train a regression model with negative values that is more stable?

I have a regression model where my target values contain roughly 60% negative values and 40% positive values. My model architecture includes a robert-large, 1 linear layer. I trained it after 1 epoch, ...
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Predicting using time-series data and static data?

I have recently been working on predicting the final value of articles on Steemit.com using downloaded data. I have a large variety of features which divide into two types. Features which change over ...
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How to make a proper approximation of Sine function with Neural Networks?

TL;DR; How to build a neural network that properly approximates the sine function with different ranges? Context and Question: From this question I decided to use the Sergey's answer, however I used a ...
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Temporal Graph Neural Network for motion prediction

Temporal Graph Neural Networks have been used for motion prediction (or traffic forecasting) in the following recent papers: Dynamic Multiscale Graph Neural Networks for 3D Skeleton-Based Human Motion ...
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time series analysis: predict number and type of service

I have temporal data regarding the number of customers who requested a specific service in a given period (month and year). Below is a small excerpt from the dataset: Month-year: month and year when ...
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Training different ML models on PLS transformed reduced-dimension inputs

I want to perform dimensionality reduction using Partial Least Squares on a complex, large-dimension data set before training various regression models on the reduced-dimension data set. I understand ...
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Is smoothing wrong in temporal predictions?

I found this paper from 2003 about predicting Forex rates: Using Recurrent Neural Networks To Forecasting of Forex. At the end of page 11, they say The network we built had two inputs and one output. ...
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Which ML algorithm is the best for predict the next PRNG generated numbers?

I have a homework. The task is to decide, if the PRNG generated lottery is attackable/crackable or not. Details: Lottery: There is a lottery game where you have to choose 8 numbers between 1-20 for ...
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What to predict in a limited transaction dataset?

I have been given a task with a real transaction dataset. The task is to predict something using either logistic regression or simple binary classification. The columns are as follow: Transaction ID ...
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Generating a dataset from data with "assumed" lables

I've got a task similar to the following: Out of x amount of people, I need to predict, who could be a good athlete and who not. The thing is, I don't have data on the athletic performance of those ...
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Should I train a neural network with data with or without a constraint?

I want to train a Neural Network (NN) using a dataset. I want to use the NN model as a prediction function in one algorithm. However, in the algorithm, any data that does not meet a specific ...
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Closed networks vs Networks with a removed delay to predict new data

I've come across two types of neural networks to predict, both from Matlab, the closed structure and the net that removes one delay to find new data. From Matlab's app generated scripts we see: % ...
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How can I predict the next number in a non-obvious sequence?

I've got an array of integers ranging from -3 to +3. Example: [1, 3, -2, 0, 0, 1] The array has no obvious pattern since it represents bipolar disorder mood swings. What is the most suitable approach ...
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How to construct a model to predict the value of a time series $y_t$ that depends from other time series $\bar{X}_t$?

I would like to know what are the standard approach to construct a model to predict the value of a time series $y_t$ that depends from other time series $\bar{X}_t$. I use to see around that for this ...
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How can I use a prediction model (e.g., ARMA model or LSTM) for multi-variate data?

I have a question I have had a dataset below ...
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Recommendation and prediction system for learning performance of students

I would like to start my master's thesis soon. The topic is "the use of collaborative filtering for creating recommendations and predictions of learning performance". I have a dataset that ...
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What is a better approach to perform predictions of time-series several values ahead?

Suppose one has a time series (univariate or multivariate) and the goal is to predict values of these series several steps ahead. I see two possible strategies: Create a model (recurrent, ...
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Has someone correctly predicted one of the variants of SARS-CoV-2 (like the Delta variant)?

Without any evidence, I have wondered it might be possible to predict the upcoming mutations of the COVID-19 virus. I am further assuming people did so. So, has someone correctly predicted the ...
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What are the standard ways to measure the quality of a set of numerical predictions that include uncertainties?

I have a radial basis function that supplies uncertainties (standard deviations) with its predictions, which are numerical values. This function is computed for a particular point by computing its ...
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Do the training and test datasets need to be equally preprocessed as one whole dataset?

I have developed, trained and tested an NLP model. It is persisted in a pickle file. The model contains the data preprocessing function that includes text cleaning and new features engineered with ...
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How to train a machine learning model with multiple attributes and one target value?

I'm working on a machine learning problem where I need to guess which customers will churn and which of them will continue to be customers. I have $X_0, X_1, X_2, X_3, X_4, X_5$ and $X_6$ attributes ...
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Machine Learning in relation to personality and behaviors predictions

I am tasked with making a machine learning model that predicts personality traits and behaviours of children based on simple and interactive quizzes. Currently I am lost and have no idea where to ...
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Predict time series from initial non-time dependant parameters

I'm trying to create an algorithm (neural network) that is able to predict a time series from a set of different parameters that are not given through time. Let's say I have a plane flying under the ...
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1 vote
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How to improve prediction performance of periodic data?

I have a 1 column dataset of $50 000$ points where 95% of the values equal $-50$. The data looks like the following: $$\begin{matrix} \text{time} & \text{value}\\ 1&-50 \\ 2&-50 \\ 3&-...
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Extracting information from RNA sequence

I am relatively new to machine learning, and I am trying to use a deep neural network to extract some information from sequences of RNA. A quick overview of RNA: there is both sequence and structure. ...
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Multi class text classification when having only one sample for classes

I have a dataset of texts, each text was identified with an ID number. I would like to do a prediction by finding the best match ID number for upcoming new texts. To use multi text classification, I ...
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Can cryptocurrency charts be estimated using neural networks?

If I were to make a neural network that predicts the value of e.g. Bitcoin tomorrow based on the chart of the last month, would that work? Of course, 100% accuracy cannot be reached, but a success ...
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Which is the best algorithm to predict the trajectory of a vehicle using lat/lon data?

I'm using Kalman Filter approaches and I've just implemented the extended Kalman filter (EKF) with my object 2D trajectory. However, I have a mess of alternative approaches that may fit better like ...
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267 views

How to do early classification of time series event with small dataset?

I would like to build a real-time binary classifier that can predict an event of interest that is occurring as soon as it starts. These are electromyographic signals, and the event classification ...
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493 views

How to deal with predictions for data outside the range of the training dataset in neural networks?

I’ve set up a neural network model to experiment with predicting foreign exchange rates based on various economic data. The model learned fine and the test data is OK ($R^2 = 0.88$). But I can't ...
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2 votes
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Predict next event based on previous events and discrete reward values

Suppose, I have several sequences that include a series of text (the length of sequence can be varied). Also, I have some related reward value. however, the value is not continuous like the text. It ...
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Root finding in Deep Equilibrium Models

In the Deep Equilibrium Model the neural network can be seen as "infinitely deep". Training learns a nonlinear function as usual. But there is no forward propagation of input data through ...
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1 answer
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How to perform prediction when some features have missing values?

Sorry if this is too noob question, I'm just a beginner. I have a data set with companies' info. There are 2 kinds of features: financial (revenue and so on) and general info (like the number of ...
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1 answer
56 views

How to use a NN for seq2seq tasks?

I am trying to make a NN(probably with dense layers) to map a specific input to a specific output (or basically sequence2sequence). I want the model to learn the relation between the sequences and ...
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2 answers
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How to train a model to predict the number of people at a certain bus stop before they cumulate in large numbers?

Each person probably uses an app that tracks his/her position periodically and sends it to our servers. What I want is to use these data to train a model to predict the rush hours of each bus-stop on ...
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1 vote
1 answer
37 views

Compressing text using AI by sending only prediction rank of next word

Is there any effort made to compress text (and maybe other media) using prediction of next word and thus sending only the order number of the word/token which will be predicted on the client side i.e ...
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2 answers
102 views

What ML algorithm should I use that suits this data?

What if I have some data, let's say I'm trying to answer if education level and IQ affect earnings, and I want to analyze this data and put in a regression model to predict earnings based on the IQ ...
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1 vote
1 answer
39 views

When is adding a feature useless?

I'm building a model, where, from a feature set A, I want to predict a target set C. I need to understand if another feature set B, together with A, can improve my model performances, instead of using ...
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2 votes
1 answer
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Which machine learning approach can be used to predict a univariate value?

I have a stream of data coming in like below (random numbers 0-9) 7, 7, 0, 0, 8, 9, 2, 7, 3, 8, 2, 8, 5, 7, 0, 8, 7, 8, 5, 3, 2, 6, 1, 9, 5, 7, 5, 3, 4, 9, 1, 3, 5, 5, 0, 7, 7, 5, 2, 8, 8, 7, 5, 5,...
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How can I predict the label given a partial feature vector?

Most of the traditional machine learning algorithms need a feature vector of a constant dimension to predict the label. Which algorithms can be used to predict a class label with a shorter or ...
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Is there a difference between using 1d conv layers and 2d conv layers with kernel with size of 1 along other than time dimension?

Let's assume I use convolutional networks for time-series prediction. Data I feed to the network have 1 channel depth, height of number of periods and number of features is the width, so the frame ...
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1 vote
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Confidence Interval around prediction with bootstrapping

I want to generate a confidence interval around my prediction (vector) $\hat{y}$. I have implemented the following procedure. However, I am not sure whether this makes sense in a statistical way: I ...
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1 vote
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38 views

3d representation of a regression with two independent variables one of them is categorical and another is continuous

I have hopefully a fundamental question of Do I understand things right. (Thank you in advance and sorry for my English which might be not so good) 1-Preambula 1: I know that if we have 2 independent ...
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2 answers
888 views

How to implement AI strategy for Mastermind

I'm looking to implement a AI for the turn-based game Mastermind in Node.JS, using Google's Tensorflow library. Basically the AI needs to predict the 4D input for the optimal 2D output ...
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2 votes
1 answer
118 views

What are modern state-of-the-art solutions in prediction of time-series?

I wanted to ask you about the newest achievements in time series analysis (mostly prediction). What state-of-the-art solutions (as in frameworks, papers, related projects) do you know that can be used ...
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What does the model predict if it has never seen the image before?

I've been messing around with an Open Set, Binary Classifier and am having trouble with it. I'm sure there are a lot of reasons for that trouble. One thing I am struggling with is, what does the ...
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0 votes
1 answer
373 views

What is the best approach to build a self-learning AI chatbot?

I am a novice in AI and I like to build a chatbot to predict diseases using patient narration as input. Initially, I simply want to train my chatbot on 1 disease only. And once this initial milestone ...
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3 votes
4 answers
548 views

How can artificial intelligence predict the next possible moves of the player?

When you play video games, sometimes there is an AI that attempts to predict what are you going to do. For example, in the Candy Crush game, if you finish the level and you still have moves ...
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4 votes
2 answers
86 views

How should I select the features for predicting diseases (in particular when patients specify their health issues)?

My aim is to train a model for predicting diseases. Now, according to this Wikipedia article, diseases are classified based on the following criteria in general: Causes (of the disease) Pathogenesis (...
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