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Questions tagged [prediction]

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

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How do nonlinear relationships affect casuality determination

Let's assume that I have only one independent variable and one dependent, and I have a great model with minimal error which deals well with predicting. Let's also assume that I do no know the true ...
Igor's user avatar
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How do I improve the prediction speed of a model?

I have a use-case where we need a classifier to take decisions in real time, meaning that as data arrives, we need to decide to which category that data belongs and it has to be done fast. The better ...
acampove's user avatar
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Calculating prediction confidence from a sequence of token-level confidences

I am working with OCSR (optical chemical structure recognition) models, and they output a sequence of token-level confidences. I am looking for a method of summarising these token-level confidences ...
finlay morrison's user avatar
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How to train a simple network to predict 2D location without knowing ground truth?

There is a 2D table of known dimension width=4cm, length=6cm. We can place a disc(diameter=0.5cm) at position (x,y). If the disc stays on the table, there is a function (evaluate_position) that says ...
goldfinch's user avatar
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Machine Learning Algorithm for identifying the factors contributing to academic performance of students

I have a dataset with several qualitative and quantitative attributes, including age, location (longitude, latitude), city, parent occupation, family size, GPA etc. My task is to find the attributes/...
Dawood Ahmad's user avatar
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Trying to use my first created Knowledge graph embeddings model

I'm trying to learn about creating and using knowledge graph embeddings models, I got a code, adapted it until I got no compiling or executing errors but now the predictions it mades are wrong. This ...
gnix's user avatar
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Predict outputs based on a variable subset of inputs

To simplify this: I have 5 columns in my dataset -> A, B, C, D and E. I want the neural network to predict the rest of the outputs based on a subset of inputs. For example: Case #1 Inputs -> (A) ...
Sam's user avatar
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Is there any justification for excluding core statistics in 'AI Death Predictor' Paper?

Over the last few days I have been seeing a lot of buzz and news articles about an AI death predictor that is 'highly accurate' based on a 'life story'. Due accuracy being such a poor indicator of ...
JimmyJames's user avatar
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Are there guidelines or rules of thumb on how to stack hidden layers in a RNN?

I’m currently working on the prediction of chaotic data and I have decided to see how well would an RNN, namely an LSTM, would do. I am fairly new to the topic of Neural Networks, but I have found a ...
Jxson99's user avatar
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1 answer
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Inquiry on Combining Two Neural Networks for unsupervised training: Has This Been Researched?

Hello AI Stack Exchange Community, I am exploring an idea related to neural networks, and I'm curious to know if this method has been previously researched or if there is a specific term for it. I am ...
Deadbeef Development's user avatar
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Can AI accurately predict specific details of criminal activity, such as when, where, and who?

Combating illegal activities is a complex challenge for societies around the world. The use of advanced technologies, such as artificial intelligence (AI) and big data, has the potential to assist in ...
Ramadhan Arif Hardijansyah's user avatar
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Mechanism of Prediction Readjustment in Supervised Learning and Role of Self-Attention in Sequence Data Relationships

In supervised learning, when the prediction deviates significantly from the expectation, how does it "readjust"? And... LLMs are a subset of deep learning, just as generative AIs are. Is the ...
Assandra Lakal's user avatar
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How much is the acceptable percentage for Random Forest in Landslides prediction?

RF had been developed to overcome overfitting in decision trees but in some cases RF still experiences overfitting in landslide prediction, which varies from 2% to 12%. How much overfitting is ...
DOROTHY's user avatar
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56 views

Is this a valid application of Autoencodeers/VAE?

I am trying to predict a spectrum (1D vector) from various scalar inputs which are known to be correlated. As the spectrum vector is very long (4000 points) it was suggested that I use dimensionality ...
Christopher McQueen's user avatar
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AI and Machine Learning Prediction Algorithms for predicting outcome results of Hypothetical poll

Can artificial intelligence and Machine Learning Prediction Algorithms assist in deciding the Outome Results of a Hypothetical Online Poll? Poll: Selecting favorite American President till date. ...
Prashant Akerkar's user avatar
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153 views

Recognize patterns within random sequences

I am familiar with ANNs as I studied them back in the days for regression and currently I'm working with CNN's for image recognition. But recently I was reading more about pattern recognition in ...
FELIPE_RIBAS's user avatar
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SCINet: how does interactive learning work?

i'm having some trouble understanding how does the basic building block of a SCINet works. In the paper the author describes the SCI-block with the following figure: In which $\phi$, $\theta$, $\eta$ ...
Juan Hirschmann's user avatar
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Purchase prediction - What minimum feature will "upgrade" A rule-based algorithm into an "AI" algorithm?

Let's say I have an algorithm that tries to predict if a given item will be bought or not, within an X timeframe, based on it's price and other attributes. To Do this right now, I'm collecting ...
thenondeveloper's user avatar
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39 views

Why "Good Model" that performs great on holdout validation data fails on production data

I have this binary regression model that has ~500 futures with an unbalanced dataset with the following results. ...
Newbie's user avatar
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257 views

How to handle out-of-bound values in Production data?

So I have this model but the data may vary. And it is virtually impossible to always have the values in bounds. If I do I`d have to use larger period leading to concept shift which is worse. The ...
Newbie's user avatar
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how to manage the impact of Covid on building a machine learning model

I need your suggestions for using historical data to build a machine learning model for analyzing the market and build an AI model(tree based model/random forest or regression analysis) for setting ...
Mahsa's user avatar
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416 views

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 ...
Edee's user avatar
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1 answer
924 views

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, ...
Việt Nguyễn's user avatar
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1 answer
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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 ...
Hans's user avatar
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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 ...
BraveDistribution's user avatar
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1 answer
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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 ...
Alfonso's user avatar
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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 ...
JoKeR's user avatar
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15 views

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 ...
Rami Hoteit's user avatar
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1 answer
52 views

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 ...
Chris's user avatar
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1 vote
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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 ...
Avishek Sinha Roy's user avatar
2 votes
1 answer
165 views

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: % ...
Verónica Rmz.'s user avatar
8 votes
4 answers
16k views

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 ...
ZenBerry's user avatar
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1 answer
54 views

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 ...
Andrea Galliani's user avatar
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1 answer
52 views

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 ...
Dae-Young Park's user avatar
1 vote
1 answer
63 views

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, ...
spiridon_the_sun_rotator's user avatar
1 vote
1 answer
67 views

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 ...
Gary 2's user avatar
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57 views

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 ...
PJ7's user avatar
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0 answers
55 views

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 ...
Annalix's user avatar
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1 vote
0 answers
289 views

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 ...
imageprocessingproblem's user avatar
1 vote
1 answer
70 views

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 ...
Thorvald's user avatar
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1 vote
1 answer
69 views

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 ...
Miguel21R's user avatar
1 vote
0 answers
47 views

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&-...
Miroslav's user avatar
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1 answer
95 views

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. ...
gollyzoom's user avatar
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1 vote
1 answer
205 views

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 ...
Fara's user avatar
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1 vote
2 answers
181 views

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 ...
Aura Lee's user avatar
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0 answers
115 views

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 ...
R2D2's user avatar
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0 votes
1 answer
533 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 ...
Hattori's user avatar
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0 answers
2k 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 ...
johnb's user avatar
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2 votes
1 answer
313 views

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 ...
Bloodstone Programmer's user avatar
1 vote
0 answers
23 views

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 ...
milez's user avatar
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