Questions tagged [prediction]

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1answer
18 views

How to get periodicity from timeseries data?

I would like to create a recommendation system for a smart home application. I gather the data in a time-series database. The app monitors the on/off state of a smart lamp and can create daily ...
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1answer
20 views

Predicting high frequency sparse time series data in python

I have a dataset of a couple of EV charging stations (10 min frequency) over 1 year. This data consists of lots of 0's, since there is no continuous flow of cars coming to charge but rather ...
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12 views

Can I use depth prediction map to infer horizontal distances?

I have a hardware + software setup that uses a sensor to give good estimates of depth, onto a pixel map - think Kinect or similar. Example below for context: Now assume I can access individual pixel ...
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14 views

Predicting in decision rules

Sequential covering is a type of decision rule procedure that repeatedly learns a single rule to create a decision list (or set) that covers the entire dataset rule by rule. Given a training dataset, ...
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2answers
17 views

Warning when plotting confusion matrix with all sample of one class

I have two arrays: the first one with all the correct labels (they are all set to zero since each sample belong to the same class) and another one with all the labels predicted by my neural network. ...
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10 views

How can I intuitively calculate the accuracy of my financial prediction model?

I've built a SARIMAX model based on my personal spendings record as a college thesis and have reached a point where I'm pretty content with how it turned out and am getting ready to start writing the ...
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9 views

Demand Prediction (Retail Sales) Datasets for Benchmarking

I've been looking for 2 days and can't seem to find what would normally appear as trivial: a Time series (preferabl daily or intra-day resolution) Demand or Sale Labelling Retail Dataset Preferably ...
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0answers
19 views

Difficulty understanding the difference between Poisson, Quasi-Poisson, and Negative Binomial models

I will try to keep this short. As an assignment for my GLM course, we were given a dataset on the # of homicide victims a person knows, as well as the race of the person. The main idea is to answer ...
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12 views

Angle prediction

I am working on an assignment for neural networks and I need to predict an angle. firstly the last layer of the neural network directly predicts the angle, secondly, the last layer gives as an output ...
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0answers
19 views

History that lead to the word “predict” being used for the application of a model on data

Background The framework scikit-learn uses "predict" for the application of model on (new) input data and I have seen many people use that term. In the scientific papers that I have read (...
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2answers
37 views

How to read the predicted label of a Neural Netowork with Cross Entropy Loss? Pytorch

I am using a neural network to predict the quality of the Red Wine dataset, available on UCI machine Learning, using Pytorch, and Cross Entropy Loss as loss function. This is my code: ...
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0answers
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Should I give regularly-spaced or irregular-timestamped data to a price predicting neural network?

I am building an application to predict the price of an item. Data is collected at regular 5-minute intervals while the application is running. Unfortunately, there is downtime, so there is not a full ...
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3answers
51 views

How to decrease $R^2$ value and change it to positive value [closed]

I'm working on a data, and use regression , as you see bellow: from sklearn.svm import SVR regressor = SVR(kernel = 'linear') regressor.fit(trainX,trainY) above ...
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0answers
98 views

Found input variables with inconsistent numbers of samples: [30, 24]

I'm using neural network machine learning and would like to see the result of my confusion matrix for my model. However, there is an error that I've got and don't know how to solve it. ...
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0answers
13 views

Unseen samples(Rare category) during prediction?

Say if I train on these features(combination of categorical and numerical data), we could see that in feature x2, sample 4 has a rare entry 'b'. if during my train test split, I end up not getting ...
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0answers
17 views

How to do prediction on survival data, using Random Forest

I should make prediction on survival data, using the random Forest method. My question is: should I follow the same approach as in logistic regression? taking into account only the status variable or ...
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0answers
16 views

Feature Engineering and prediction with R and python

I have a sequential dataset, and have 2000 rows for 300 ID. I have 20 variables (i.e in my real dataset) ...
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1answer
20 views

How to use prediction model after onehot encoding?

I have created a prediction model for this dataset ...
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2answers
179 views

Speed up Keras Model Prediction Load Times

I am trying to create a prediction API using keras which loads the model predicts and closes the model. But initializing time in python is about 3-5 secs so each request takes around 5 secs to return ...
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13 views

Preparing and combining datasets for predictions

I am trying to create and train a model to predict the winner of a professional DOTA match. This model is only for "fun" and shouldn't be used for ...
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1answer
49 views

How to reconstruct a scikit-learn predictor for Gradient Boosting Regressor?

I would like to train my datasets in scikit-learn but export the final Gradient Boosting Regressor elsewhere so that I can make predictions directly on another ...
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0answers
26 views

How to predict out-of-sample observations with depmixS4 package in R?

I have a series of univariate data and I want to fit a Hidden Markov Model on it using the depmixS4 package on R. My final goal is to predict the next k observations (let's say k = 10) for the data ...
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1answer
89 views

Encoder-Decoder LSTM for Trajectory Prediction

I need to use encoder-decoder structure to predict 2D trajectories. As almost all available tutorials are related to NLP -with sparse vectors-, I couldn't be sure about how to adapt the solutions to a ...
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0answers
63 views

LSTM giving almost constant output

I have used an LSTM with 4 layers deep each layer having 10 LSTM units to predict the AAPL stock 500 steps away by looking 50 steps back and it was predicting well (only a lag was there). However when ...
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2answers
61 views

Predicting the likelihood that a prediction from a linear regression model is accurate

So to set up the problem: I have a data set that had labeled data like colour, brand and quality as independent variables and the dependent is RRP (price). I have made a linear regression model using ...
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2answers
28 views

Can we consider high correlation to be a good predictor?

The problem of predicting the daily number of COVID-19 cases is indeed challenging and many (external) factors should be taken into account to come up with a reasonable predictor. However, we have ...
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1answer
23 views

Predicting invoice data of 12 month using only 1 month data

I have only 1 month of historical data of invoices can I predict next 12 month of data with good accuracy if it is possible then which model should I used for prediction? Thanks
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0answers
29 views

Is padding the right way to allow your model to make prediction with test sequences of shorter lengths?

Say I have a RNN-lstm encoder-decoder model trained on fixed timesteps (no padding when training, all sequences are treated as if having the same lengths). My testing criteria requires me to provide ...
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1answer
22 views

Does my prediction improve when I use more, but worse classifiers?

I have a logical problem when programming my tumor identification algorithm. In my data sample, I have tested multiple antibodies on tumors - to identify whether those tumors are good or bad. This is ...
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0answers
30 views

Predicting next rows in tabular dataset

I have a tabular dataset of financial transactions with a target binary variable 'isFraud' which indicates if the transaction is fraud or not. I want to build a model that given some past trasactions, ...
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0answers
20 views

Effect of batch during prediction

During prediction (not training), is it normal to get different loss for different batch size? Worst case happens when I use batch_size=1 for test dataset. The prediction performance get pretty bad. ...
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0answers
14 views

Confidence interval for class membership probabilities

I would like to calculate confidence intervals for predicted probabilities of a class membership obtained with randomForest. I know I could use predict.all in randomForest(), which gives me the ...
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0answers
30 views

*(CATEGORIES[int(prediction[0][0])])* giving me different result for single image prediction from saved model

From a saved model, I am trying to predict a single image. I followed this code - https://www.youtube.com/watch?v=A4K6D_gx2Iw I am getting different result for two different command- ...
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2answers
80 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
42 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
21 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
87 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
33 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
18 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
48 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
33 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 ...
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1answer
42 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
56 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
116 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
66 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
153 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
61 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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