Questions tagged [prediction]

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100 views

how do I predict the next's alarms ? (time series) [closed]

I'm trying to solve a time series forecasting problem, where the main goal is to read data with various alarm logs and make a prediction about what may happen in the future. Specifically, my data is a ...
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1answer
44 views

Algorithm for Multivariable timeseries prediction (COVID forecast)

I am trying to forecast tomorrow's COVID-19 cases in my country. I tried a simple Linear Regression implementation based on the "new_positives" field but it does not work very well. I had ...
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1answer
38 views

Predict real world data after modelling with scaled features [duplicate]

I trained and test a model with scaled features. Now, I want to predict a single real world sample. If I have one sample alone, I can't scale it to fit into the model like I did with the test data. I ...
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1answer
152 views

Is it possible to predict sentiment of unlabelled dataset using BERT?

I have a large unlabeled dataset and I want to predict sentiment for each document in this dataset. I want to know, is it possible that I can use BERT for sentiment analysis of unlabeled data? I have ...
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1answer
34 views

target variable prediction among possible answers

I have a dataset on which I would like to apply a Machine Learning algorithm for multi-class classification. An example of my target variable (in string format, will be later ...
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0answers
29 views

What algorithmic solution would you use for this scenario?

The Project In a Nutshell Use an algorithmic solution to predict with 70%+ accuracy in as close to real-time as possible the increase and decrease of at least three numeric incremental movements for a ...
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0answers
20 views

Why does my model fail to predict on the whole dataset?

So I have about 3000 images with 6 classes and this is what I did: 1 - split into training set and test set prior to anything with 20% test size 2 - performed data augmentation on the under ...
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1answer
50 views

Sir Rod Stewart's and Celine Dion's voice after 15 years i.e. Year 2035 [closed]

https://www.google.com/search?sxsrf=ALeKk03hQn_rH1aaf7yO0q7CgN7CxPw2vw%3A1601345036018&ei=DJZyX9BW_o_j4Q-Fn77QCg&q=rod+stewart+age&oq=Rod&gs_lcp=...
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1answer
56 views

How to approach the dataset with a continuous and discrete label?

Let's say you're predicting the amount of money to bet in a poker game. Based on the game situation, you might decide to fold. In that case, the amount of money to bet is zero. If you decide to call ...
1
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1answer
46 views

Regression performance varies hugely on shuffling training and testing data

I'm working on a regression problem to predict a variable y based on an input vector X with about 10 columns. To split the data for training and testing, I use the ...
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1answer
65 views

Predicting game scores using sklearn

I am using onehotencoding and RandomForestRegressor to predict scores of a set of soccer games. How can I use it into ...
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1answer
125 views

Understand the equations of quantile regression forest (Meinshausen)?

I am trying to implement a quantile regression forest (https://www.jmlr.org/papers/volume7/meinshausen06a/meinshausen06a.pdf). But, I have some difficulties to understand how the quantiles are ...
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1answer
84 views

How to use a multiple linear regression model built from normalized data

I built a linear multivariable regression model from normalized data (for the interval [0; 1]). Initially, the data was not normalized, I normalized the data by myself (independent and dependent ...
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1answer
196 views

Machine Learning: Predicting target based on a feature

I have a df looks as follow: -It is very likely that the same feature1Xfeature2Xfeature3 combination will appear multiple times....
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0answers
10 views

Estimating the progress through a workflow with an arbitrary number of steps

I have a dataset where a record (a customer order, to choose a made-up example) goes through a set of steps until eventual completion. The set of steps is generally very similar, with small variations ...
1
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1answer
114 views

LSTM model prediction scaling with loaded model

I am deploying a LSTM pytorch model for production and I have issue with scaling the LSTM output correctly. While the model was tested the output was scaled with label data: ...
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0answers
19 views

Stabilize Neural network prediction for class probability

I could not carry my question from stackoverflow I ve been trying to fit a neural network for binary setting using library(keras) and I am interested in class ...
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2answers
206 views

How to predict unknown unknowns in machine learning

I am dealing with a problem about classifying bird species through analysing MFCCs. I already built a dataset with 13 MFCCs for two kinds of birds. And I trained the data with Naive Bayes & KNN ...
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0answers
41 views

Why NARX neural network and Hammerstein-Wiener model perform worse than simple sigmoid network nonlinearity estimator on any predictions?

I am currently working on dynamic modeling and exploring different techniques and algorithms to deploy a dynamic time-series black-box model. My data looks like the following: I have 7 inputs and 1 ...
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0answers
81 views

Predict how many days until New Purchase

I am trying to introduce myself into predicting with dates and I am having big troubles understanding how to do it. I have a dataset with customer orders from an e-commerce platform with the usual ...
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0answers
181 views

Keras Predictions as a list of file names for each class

I've created a model using Keras, I have trained it with a training and validation set, and have used a test set filled with random number of images for each class. My test set consists of one folder ...
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0answers
44 views

Binary classification of multiple Sequences using Keras

I am trying to classify multiple independent sequences using Keras. My data looks like this (example with different stocks and their values). ...
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1answer
142 views

Predicting equipment failure with time series alarm data

I am trying to predict machine failures based on alarm data. The situation: There is approximately 4000 machine failures per year. These are labelled poorly (it is entered manually and can have ...
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0answers
22 views

Improve confidence interval accuracy

I am doing a linear regression on log-transformed data and I use the bayesian approach to model the predictive distribution and construct my 90% prediction Interval. The problem with this approach is ...
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1answer
51 views

Predicting next element of a sequence given small amount of data

I have data of bank branches and amount of revenue they have generated in a month. The data looks like this: I am tasked to find the expected revenue for the branch for the next month using machine ...
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0answers
78 views

Why are Neural Network predictions “correct”, but offset from true value? Not using any past lagged values

I recently asked a similar question, but didn't get a response that really addressed/fixed the issue. Additionally, I've done some more work since then. I'm sorry for the long question below, I just ...
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3answers
3k views

Why are predictions from my LSTM Neural Network lagging behind true values?

I am running an LSTM neural network in R using the keras package, in an attempt to do time series prediction of Bitcoin. The issue I'm running into is that while my predicted values seem to be ...
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2answers
209 views

Why my training and testing set are about 99% but my single prediction does wrong prediction?

I have performed fruits classification using CNN but i am paused at a point where all things are going right confusion matrix accuracy score all are correct it seems there is no overfitting but it ...
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2answers
106 views

Machine learning to predict pollution at a single location

I have 2 months of air pollution measured data for a location of interest. I am highly interested to play with machine learning algorithms to predict pollution at the same location (let say, for the ...
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1answer
148 views

Can 1D-CNN method apply to real-time time series classification?

So I got an EEG dataset with shape (data points, 19), each row's shape (1,19) represent 1 second of EEG. I read much research on EEG classification that used many Deep Learning method and 1D-CNN is ...
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1answer
21 views

Predicting evolution of an unknown mathematical function with machine learning?

Is it possible to predict how a mathematical function evolves using ML? I am studying radioactive decay of polonium 210 and I have gathered data for its decay throughout a couple of weeks. I was ...
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2answers
59 views

Ingredients, Recipes and recipe ratings. I would like to predict the rating based on combination of ingredients

I would really appreciate some help on the first steps to my problem, suggestions of modeling techniques i could use or relevant research (i could not find any). I have a list of ingredients (150 in ...
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1answer
1k views

Multivariate, Multi-step LSTM time series forecast

I'm trying to predict the Pollution using a Multivariate and Multi-step LSTM code, I've been following this tutorial. I've been following the code until the end, but couldn't understand where the ...
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1answer
169 views

Keras Model Predict is not predicting all images flowing from directory?

I have the following code where I have done all the training and passed the testing set as a flow from directory. After that when I pass that object into the model.predict option, the array received ...
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1answer
38 views

best NN architecture for point prediction

I'm training to predict a single value y (continuos in [0,1]) based on a number of variables ...
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1answer
31 views

Prediction for not completely well classified data

I have a DataFrame of users, some of them are "bots" and they are identified with a bit equal to 1 in the "is_bot" column, if the bit is 0, the user is considered as "human". The problem is that some ...
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0answers
23 views

When should I reverse normalizations to evaluate loss?

If I am training a neural network and have normalized the data before-hand, should I reverse the normalization to calculate the loss? This tutorial provides an example of this method. What if I'm ...
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0answers
11 views

Measuring chance (“risk”) of being in some class

I don't know if this question fits better here or in statistics, but I think here is more appropriate. I have a dataset with several companies and its features and also I have the information if they ...
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1answer
43 views

Two-class model with predicted scores needed - classification or regression approach

In my problem, step one is to build a model to classify cases as one of True or False (1 or 0 could also be used obviously). Once the optimum model is found, step two is to retrieve probabilities for ...
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1answer
61 views

How to measure model success in production

I have a model running on a productive system. The model predicts if some lead will become a sale. How would you develop a check, which checks the success and the accuracy of the model? There is a ...
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1answer
309 views

Why is predict_generator is returning an empty array?

I am trying to print the predicted labels of my test data but the predict_generator() function is returning an empty array. My Model: ...
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1answer
71 views

How to use spectral clustering to predict?

In an academic paper, they talk about using a nearest neighbour algorithm to predict the cluster of a new point. And how the number of nearest neighbours is set to 10 in their example. What do they ...
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1answer
151 views

YOLO Dense Prediction

I have two questions about dense prediction in YOLOv4 paper What does it mean by the (hard negative, online hard) example mining method is not applicable to one-stage object detector, because this ...
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2answers
225 views

why we sample when predicting with Recurent Neural Network

I trained a Recurrent Neural Network to predict the next word in a sentence. I trained and now I want to predict, but there is something I am not getting well. I saw it in many tutorials even in the ...
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1answer
2k views

How to make predictions of multiple input samples at once in tf 2 with keras

I am quite confused on the output of model.predict when after training I validate my model on around 6000 samples I use the following pseudo code: ...
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1answer
57 views

I am getting very minimal mse values and not sure if it is correct?

Below is the linear regression model I fitted and not sure if I am doing the right way as I am getting neat to 99% accuracy Fitting Simple Linear Regression to the Training set ...
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0answers
22 views

Derivative of multi-output Gaussian Process

I am working on a project where I estimate transition and measurements models for a kalman filter using Gaussian Processes. In order to linearize the models I require the Jacobian of the estimated ...
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0answers
91 views

Keras Bidirectional LSTM: low training and validation loss but very bad predictions

I'm training a Bidirectional LSTM using Keras. My task is to predict the words order in a sentence, so, given a sentence, ...
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0answers
281 views

PyTorch time series prediction beyond test data

I am currently playing around with pytorch models for time series prediction. I have managed to successfully run a model to predict test data. I was wondering how can I use it to predict beyond test ...
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2answers
802 views

Why do decision trees have low accuracy?

It seems to be generally acknowledged that decision trees have low prediction accuracy. Is there a concise explanation for why they have low accuracy? I've read this so much, I've accepted it to be ...

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