Stack Exchange Network

Stack Exchange network consists of 174 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.

Visit Stack Exchange
Join us in building a kind, collaborative learning community via our updated Code of Conduct.

The tag has no usage guidance.

1
vote
1answer
14 views

Train an LSTM neural network with time series containing seasonal and trend

I am working on a project for predicting the number of DNS queries from the site: DNS queries statistics. The data I use is minutely data, which means the number of DNS queries of every minute. If ...
1
vote
0answers
6 views

Naive/ Persistent Models & 7 Day Forecasts

When determining the baseline performance using a persistent or naive model I understand it to be using the value of the previous time step as the prediction for the next time step and then ...
0
votes
0answers
24 views

Time Series prediction with multiple features in input data

Assume we have a time-series data that contains the daily orders count of last two years: We can predict the future's orders using Python's statsmodel library: ...
1
vote
0answers
13 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: ...
0
votes
0answers
41 views

What all methodologies are there in Data Science/ML to predict the next transaction date of a customer?

I've a data-set with three columns: customer_id, transaction_date & sales_amount. Product data can also be added but to avoid complexity, I've not added that. The objective on which I'd like to ...
5
votes
1answer
55 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 ...
0
votes
0answers
26 views

Explaining ROC curve

I am running classification algorithm on binary class classification problem where I achieve ~85% precision and ~84% recall rate. My issue is that ROC score looks quite edgy and there are only few ...
0
votes
2answers
29 views

Why does prediction by a consensus of classifier work better than prediction by a single classifiers?

I have seen that consensus of classifiers (taking say 5 separate classifiers) and obtaining the final labeling of the unknown sample based on the voting method (whichever class gets the predicted the ...
1
vote
0answers
9 views

How to decide which forecasting model to use? [closed]

So I have a sales forecasting problem where I have 3 years worth of data about weekly sales of a certain company. There are 3 types of retail stores in that company, Type A, B, and C. There are a ...
0
votes
1answer
14 views

Inference of root mean square value in terms of house prediction

The objective of the task is to predict the housing prices. A model is created based on California housing dataset to predict housing prices and is subjected to evaluation using the below code. ...
2
votes
0answers
22 views

Predict time series using NN trained with multiple TS [closed]

I'm trying to predict time series using RNN from keras and I have several time series to work with (these are sales from some stores, just usual 1D TS). Right now I can train one simple model using ...
0
votes
0answers
65 views

Tensorflow - Clarification on how to predict more than 1 step ahead using LSTM

I'm looking for some clarification on how to perform more than one prediction ahead using long-short term memory in Tensorflow for univariate time series. The reason is that I'm having problems when I ...
0
votes
1answer
29 views

How can we define missing rating in recommender system?

I was reading about collaborative filtering where we need to pass (user, item and rating) in case of matrix factorisation (SVD). Now, my question is given data of ...
0
votes
3answers
103 views

Forecast vs Prediction: What is the difference?

I use the two terms as follows: A prediction model gets features (which can be a time series) as input and gives a fixed-length output (might be multiple values, but "atomic" in some sense) Examples:...
1
vote
0answers
24 views

Predicting a new document [closed]

I have a document, (purchase agreement) of approx. 100 pages. This document is sent from buyer to seller several times, and each time there is a negotiation. Negotiation could be anything. For eg. ...
1
vote
1answer
47 views

Predicting Customer Activity Absence

Could you please assist me with to following question? I have a customer activity dataframe that looks like this: It contains at least 500.000 customers and a "timeseries" of 42 months. The ones and ...
0
votes
2answers
35 views

Estimate battery voltage based on scheduled events and previous behaviour

My goal is to estimate if a battery will have enough charge for certain other systems to be powered. The power state of the other systems is recorded (i.e. if they are turned on or not), as well as ...
0
votes
0answers
22 views

Real-Time signal processing with RandomForestClassifier in sklearn

I am trying to perform real-time decision making on data from a radar sensor and trying to detect occupancy. I generated data using the same sensor annotated it manually as vacant or occupied. I ...
1
vote
1answer
21 views

How do I use rnn to forecast to n periods with limited data?

So this is my 1st time trying to run a small time-series dataset through an RNN, but after a lot of searching, I haven't been able to find, 1. How I can use this to forecast to n periods ? (like in ...
1
vote
0answers
21 views

Orange: Predictions widget on same data gives different results

I have built a simple tree predictor and then applied this to a new set of data. This was giving a very different probability distribution so I tested connecting the same training data and comparing ...
1
vote
1answer
23 views

How to predict next year's gross revenue given this year's data?

I have the following dataset (.csv format) which contains: 100 columns: $\textbf{Period}$ (in years, e.g. 2017, 2018, ..., 2028), $\textbf{Gross Revenue}$, $\textbf{Region}$ (e.g. APAC, NEMEA, etc), ...
1
vote
1answer
22 views

Predicting which apps users may be interested in

I am building a mobile app that can predict what apps users may be interested in downloading from the play store, based on what apps the user has already installed on their device and how much time ...
2
votes
1answer
241 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: ...
2
votes
0answers
21 views

Prediction questions related to the dataset

I have been self-learning data science from different sources. I have a dataset which was sent to me by my friend from one of her college courses. The work is to be done in R preferably. Description: ...
0
votes
0answers
288 views

In Keras how to get the `class_indices` or prediction labels for an existing model

I know that keras provides a .class_indicies dictionary containing the mapping from class names to class as part of ...
1
vote
1answer
31 views

Visitor's probability to purchase on eCommerce site, based on aggregate historic data

On an eCommerce website we want to create some personalization for visitors who are more likely to make a purchase. Let's assume we only have one single item for sale. The likelihood should be based ...
0
votes
0answers
25 views

Support Vector Regression (SVR) for spatio-temporal prediction

I know that SVR can ensure spatial prediction from one side and can do time series prediction from other side but can SVR do both : tempospatial prediction at the same time?
1
vote
0answers
122 views

Test data predictions yield random results when making predictions from a saved model

I am classifying aerial imagery that is tiled into 256x256 tiles using Keras and TensorFlow. The model splits the training data (i.e. the 256x256 image tiles making up the study area) into 70% ...
1
vote
0answers
14 views

Choosing the right prediction method

i have a data set with personal properties (age, education etc.), and each entry in the dataset is associated with a list of websites and daily visit. my goal is to predict for a given person the ...
6
votes
1answer
619 views

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

I just built this LSTM neural network with Keras ...
1
vote
0answers
37 views

spatiotemporal prediction using support vector regression

i am using a geographic dataset and i intend to use SVR as machine learning method for predicting spatiotemporal patterns from this dataset. My question is does SVR canensure spatiotemporal ...
1
vote
2answers
35 views

Group prediction

I have following sort of data coming every day: (0)(3,4,5)(6,9,1)(5,35,12,232) (1)(5,1,4)(6,2)(12,54,12,43)(8,23,65) (2)(6,7,2)(34,3) (3)(4323,23,12,4543) (4)(987,32,324,23,224,12,213,21)(1,2) (...
0
votes
1answer
92 views

Error in training a merged model in Keras

I attempted to merge a VGG-16 and ResNet-50 model in Keras to benefit from the combined feature representations toward a binary classification task. I was successful in building and saving the merged ...
2
votes
0answers
35 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. ...
0
votes
3answers
79 views

k-means: Only one-dimensional cluster predictions in two-dimensional space

For this dataset, it seems that the predictions of my k-means model only consider the horizontal axis, although the cluster centers seem reasonable. Is something wrong with this classification? ...
0
votes
1answer
53 views

predict() function in R

While predicting, what happens if we pass the newdata along with the target variable? Do we need to isolate the target variable before feeding into predict function?...
3
votes
1answer
124 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 ...
0
votes
0answers
11 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 ...
0
votes
1answer
23 views
0
votes
0answers
30 views

getting prediction as array like [0. 0. 0. 0. 0. … 0. 0. 0.] even accuracy in test data is above 70%

I am using sklearn's preprovided classifiers for training ,my data, i have used bag of words model to make data. I have used technique TF-IDF to normalize my data. The classifier i used is mainly :- ...
0
votes
1answer
66 views

what is the best approach to my prediction problem

I'm trying to predict occupancy for every floor in a building (with the primary focus on only one "proof of concept" floor for now). I have a lot of time-series data, that tracks user's logons and ...
1
vote
3answers
79 views

Whats an explanation of PCA that is intuitive for someone in senior leadership who doesn't have a technical background?

I've been pulled onto my first Data Science project at work. Classic problem of predicting sales based on web traffic data, etc. While I don't know about the specific techniques I will be using in my ...
0
votes
0answers
30 views

Statistical Model

I have agents’ insurance data. I want to measure agent sales performance and alert his/her superior when the agents/agency unit is under perform. The available variable are channels, regions, state, ...
0
votes
0answers
15 views

What is the best datastructure for more dimensional timeseries prediction?

I'm working on a prediction model for quarter hourly traded electricity contracts. Therefore the usual timeseries based approach won't work. What I want my structure to look like: \begin{array} {|c|...
0
votes
1answer
185 views

Can LSTM have a confidence score for each word predicted?

LSTM networks can be used to generate new text. Given a sequence, I can predict the next word. Is there a way to get a score associated to each word predicted? In particular, if the new word has ...
0
votes
0answers
21 views

User Behaviour Prediction

Data Let's say each User have array of Page visited Time on page And each User labeled as Purchase-A (Have already purchased) Potential (Never Purchase) Purchase-A & Purchase-C (Purchased ...
0
votes
1answer
20 views

Data preparation for Regression Model

Hi I'm currently trying to predict if an item will be successful in my store, this means (How much is going to sale in USD) My training dataset contains many features: Item name Item weight Item ...
0
votes
1answer
244 views

Predictions with arbitrairy sequence length for stateful RNN (LSTM/GRU) in Keras

I have time series data of the following properties: input shape: (num_timesteps, num_features) output shape: (num_timesteps, num_outputs) I reshape it to batch ...
0
votes
0answers
8 views

ARMA model with i) many zeros and ii)always positive values

Two questions on a data I have that I am fitting an ARMA(p,q) model with. My data has lots of zeros (it is a solar energy prediction and I know between 10 PM and 6 AM it must be zero). I fit a ARMA ...
0
votes
0answers
52 views

Predictive model(s) to predict outputs at a future time $t_1$, given the predictor and output values at time points $t_0,t_1$?

Cross posted at- https://stats.stackexchange.com/questions/332759/predictive-models-to-predict-disease-at-a-future-time-t-1-given-the-predict, mentioning it to respect the guidelines. We've $N$ ...