Questions tagged [prediction]

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81
votes
5answers
53k views

Time series prediction using ARIMA vs LSTM

The problem that I am dealing with is predicting time series values. I am looking at one time series at a time and based on for example 15% of the input data, I would like to predict its future values....
17
votes
4answers
13k views

Prediction interval around LSTM time series forecast

Is there a method to calculate the prediction interval (probability distribution) around a time series forecast from an LSTM (or other recurrent) neural network? Say, for example, I am predicting 10 ...
16
votes
1answer
16k views

What do “compile”, “fit”, and “predict” do in Keras sequential models?

I am a little confused between these two parts of Keras sequential models functions. May someone explains what is exactly the job of each one? I mean ...
12
votes
2answers
4k views

Is a 100% model accuracy on out-of-sample data overfitting?

I have just completed the machine learning for R course on cognitiveclass.ai and have begun experimenting with randomforests. I have made a model by using the "randomForest" library in R. The model ...
12
votes
1answer
13k views

How to Predict the future values of time horizon with Keras?

I just built this LSTM neural network with Keras ...
7
votes
1answer
5k views

how to interpret predictions from model?

I'm working on a multi-classification problem - Recognizing flowers. I trained the mode and I achieved accuracy of 0.99. To predict, I did: ...
6
votes
2answers
11k views

Why is input preprocessing in VGG16 in Keras not 1/255.0

I am just trying to use pre-trained vgg16 to make prediction in Keras like this. ...
5
votes
3answers
989 views

Why can't my neural network learn how to predict the squares of natural numbers?

I want my neural network to learn to predict the square $n+1$ number having $n$ number. I am considering a regression problem. That's what I'm doing: ...
5
votes
2answers
1k views

Is There a Way to Re-Calibrate Predicted Probabilities After Using Class Weights?

I have classification data with far more negative instances than positive instances. I have used class weights in my models and have achieved the discrimination I want but the predicted probabilities ...
5
votes
1answer
778 views

Calculate confidence score of a neural network prediction

I am using a deep neural network model to make predictions. My problem is a classification(binary) problem. I wish to calculate the confidence score of each prediction. As of now, I use ...
5
votes
2answers
8k views

Using RNN (LSTM) for predicting one future value of a time series

I have been reading several papers, articles and blog posts about RNNs (LSTM specifically) and how we can use them to do time series prediction. In almost all examples and codes I have found, the ...
5
votes
3answers
358 views

Which algorithm to use for efficient resource assignment?

I am a starter in ML. So pardon me if the question is naive. We have a Project Management tool where users can create a ticket and assign it to others. This is just one part of the tool but we are ...
5
votes
1answer
3k views

Batching in Recurrent Neural Networks (RNNs) when there is only a single instance per time step?

I have scoured the internet and books, but everything seems to use num_steps and batch_size or similar terms interchangeably and ...
5
votes
3answers
252 views

How to create an ensemble that gives precedence to a specific classifier

Suppose that in a binary classification task, I have separate classifiers A, B, and C. If I ...
5
votes
1answer
118 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 ...
5
votes
1answer
142 views

which algorithms can be used to extrapolate non-linear data?

I have a dataset, where target value changes in time in following way: I need to predict target value for upcoming month, however I struggle to find a method to extrapolate the function that defines ...
5
votes
2answers
9k views

Prediction Intervals Using XGBoost

I want to obtain the prediction intervals of my xgboost model which I am using to solve a regression problem. I am using the python code shared on this blog, and not really understanding how the ...
5
votes
1answer
66 views

Theoretical background for model arhitecture choosing

Suppose I have a dataset $X$ and two different binary labels $y_{1}$ and $y_{2}$. The classes are very imbalanced - 3% of true in $y_{1}$ and 2% in $y_{2}$. Moreover, there are no pairs of (0,1), so, ...
4
votes
2answers
3k views

Encode multi-class response variable

In a classification problem when the response variable has multi-class, e.g., "sunny","rainy","cloudy", how should we encode it? I know that for predictors like this, usually we do One Hot Encoding, ...
4
votes
1answer
58 views

Why does MAE differ after prediction (Neural Network)?

I'm having trouble understanding what's happening in the following code. I already have defined x_train, y_train, x_val, y_val and x_test which define my training, validation and test sets. I'm using ...
4
votes
2answers
220 views

Scikit-learn pipeline with scaling, dimensionality reduction, average prediction of multiple regression models, and grid search cross validation

I would like to use a sklearn pipeline doing this : ( - ) scale the data ( StandardScaler ) ( - ) reduce dimensionality ( PCA ) ( - ) make a prediction with GradientBoostingRegressor() and ...
4
votes
1answer
59 views

How to construct confidence bound for Time Series Prediction?

I have some time series data and am using some Deep Learning techniques to get its prediction. Now, I would like to construct confidence bounds for it. I calculated the residuals, their mean and ...
4
votes
2answers
100 views

Is ARIMA appropriate for time series prediction involving a mix of explanatory and independent variables?

I have a table with the following columns: Date(Month,Year), Sold_Past_Month, Quantity_Available, Quantity_Shipping_In, Missed_Sales, Quantity_Needed Quantity_Needed is the dependent variable that ...
4
votes
3answers
5k views

tsne for prediction

I have a traditional prediction setting, with a training data set train and a test data set test. I do not know the outcome <...
4
votes
1answer
215 views

Why does CV yield lower score?

My training accuracy was better than my test accuracy, hence I thought my model was over-fitted and tried Cross-validation. The model further degraded. Is that my input data need to be sanitised ...
4
votes
0answers
3k views

Kalman filter for time series prediction

I have the information about the behaviour of 400 users across period of 1 months (30 days). Across those 30 days I measure 4 different information (let's call it A,B,C and D), hence I have a total of ...
3
votes
3answers
2k 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 ...
3
votes
1answer
6k views

99% validation accuracy but 0% prediction results (UNET Architecture)

I am debugging results from the UNET architecture that I am using for identifying corneal reflection in eye images. While I am getting over 99% training accuracy and also very high (over 99%) ...
3
votes
1answer
6k views

Simple prediction with Keras

I want to make simple predictions with Keras and I'm not really sure if I am doing it right. My data looks like this: ...
3
votes
2answers
1k views

Very low probability in naive Bayes classifier

I have designed NB classifier from scratch in python for binary classification problem. There are total 220 records out of which 85 records belongs to 'Yes' class and 135 to 'No' class. My classifier ...
3
votes
1answer
99 views

Make classification and prediction at the same time

I am working on the detection and prediction of epileptic seizures and I was thinking about something : would it be possible to apply classification and prediction at the same time. I mean, having ...
3
votes
2answers
10k views

Sales prediction of an Item

So, I've been trying to implement my first algorithm to predict the (sales/month) of a single product, I've been using linear regression since that was what were recommended to me. I'm using data ...
3
votes
3answers
583 views

When is it convenient dropping duplicates when performing Time Series Prediction?

I have this Dataset. ...
3
votes
2answers
368 views

Sports prediction using machine learning [closed]

I am trying to predict soccer scores using past results. The dataset I have only consists of the home team, the away team, goals scored by the home team and goals scored by the away team in each match....
3
votes
1answer
1k views

How to properly predict date using Orange 3

First of all - I'm new to all of this. I'm trying to create a model to predict the release of ios 12 based on previous years. I've got an excel that has a format like this: ...
3
votes
2answers
252 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 ...
3
votes
1answer
85 views

Terminology - regression with one output and multiple output variables

I am trying to predict the response when the input is represented by Fourier transform. These form the features and are typically represented as a vector, $x_1,x_2,...,x_d$ where $d$ is the length of ...
3
votes
1answer
33 views

Predicting probability for each tag given already chosen tags

I have a set of tags (~10'000, will be extended over time) presented to a user. After he has selected 3 or more tags, I want to predict for each remaining tag what the chances are that the user will ...
3
votes
1answer
705 views

Use Machine Learning/Artificial Intelligence to predict next number (n+1) in a given sequence of random increasing integers

The AI must predict the next number in a given sequence of incremental integers (with no obvious pattern) using Python but so far I don't get the intended result! I tried changing the learning rate ...
3
votes
1answer
104 views

How can i find trend time for my articles?

our article is time-based, that means is my article search more in a specific time. as you can see in under chart this article search more in specific period time. if my dataset looks like this(it ...
3
votes
1answer
3k views

Time series prediction of discontinuous data

In the context of time series prediction, I have read that time series is a series of data that taken at successive equally spaced points in time (which means its in order). What if I have a ...
3
votes
1answer
2k views

Estimating Predictive Uncertainty for unlabeled data

I am trying to estimate the predictive uncertainty for a deep neural network. While I do have a labeled training set, I´m trying to measure uncertainty for some unlabeled production data. This paper ...
3
votes
1answer
2k views

Tensorflow predicting same value for every row

I have a trained model. For single prediction I restore the last checkpoint and pass a single image for prediction but the result is the same for every row. Does anyone have a clue of what might be ...
3
votes
1answer
59 views

How to prevent a neural network from outputing too clustered probabilities?

I have a CNN outputting probabilities using a logistic output. The performances are good on the test set. Yet the probabilities it outputs are very clustered, they are either 0 or 1! I would like ...
3
votes
2answers
112 views

Prediction approach on unique data or progressive data

In a employee attrition analysis with a table having rowwise data for a (employee like Id, name, Date_Join Date_Relieving Dept Role etc) ...
3
votes
1answer
3k views

Making predictions / Loading model in TensorFlow 2.0

I use TensorFlow/Keras on a daily basis to make predictions for a project. Everything works fine but I was getting regular warnings about the transition to TensorFlow 2.0 and I thought this week I ...
3
votes
0answers
47 views

Timeseries prediction error measurement. How to deal with diffrent time scales?

I have some time series and a prediction model. Now I would like to measure how good/bad the prediction is for different products. The problem is that for each product the time points (frequency of ...
3
votes
0answers
162 views

Next events prediction based on previous events

I have data set of sequences of user executed commands sorted in the order of its occurrence. The data looks like this. ...
2
votes
1answer
9k views

Accuracy for Kmeans clustering

I am looking for accuracy python code for kmeans clustering with no labels. Is there anyone who knows about it? it is ok that is not built-in function. Manually made is also ok
2
votes
1answer
4k views

Predicting with categorical data

I have a dataset which contains various columns: numerical and categorical. Dataset here: I was able to process the categorical data using .astype('category') and ...

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