Questions tagged [time-series]

Time series are data observed over time (either in continuous time or at discrete time periods).

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420 views

Time-stamp for linear model

How can we extract information from time-stamp variable for modelling? I have a variable with format mm-dd-yyyy hh:mm:ss I want to predict an outcome variable using time-stamp as input variable. I do ...
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1answer
86 views

Account for unknown error in time series data

Given: Time series data collected from sensors. There is an unexpected gradual drop in the initial data when sensors are idle. However, this drop is not so visible when sensors are active because ...
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55 views

Forecasting daily usage of a prouct

Lets say that you have panel data, of daily consumption of product p1 of 10000 individuals. The panel data is on a daily basis for only one month, this means that $t=1,...,30$. The question is how do ...
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343 views

Visualization: Changing group memberships over time

I am looking for an interactive visualization. I have store classification based on their sales (sales buckets) for multiple quarters. I want to visualize The size of each bucket for every quarter ...
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1answer
473 views

Find outliers in time-series data

I want to find outliers in power consumption in real-time, at hourly rate, i.e., at the end of the hour, I should say whether power consumption in current hour was outlier/anomalous or not. Approach: ...
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1answer
849 views

Compute Baseline/Representative of Time-Series Data

I have time-series data of 10-days for the same time interval as shown in below figure. Here it shows one-hour power consumption for 10 days. Data is sampled at 10 minutes rate. I need to show this ...
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2answers
461 views

Spark Scala alternative Machine Learning Library?

I’m using Spark Scala for multiclass classification, and features are continuous. MLlib seems to be limited to Decision Tree and Random Forest for this type of classification – for Naïve Bayes, ...
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2answers
593 views

Time Series Forecasting with Neural Network (mixed data types)

I have a dataset with the following format: TimeStamp | Action | UserId 2015-02-05 | Action1 | XXX 2015-02-06 | Action2 | YYY 2015-02-07 | Action2 | XXX ... I ...
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1answer
483 views

If a time series has random time events, how to detect patterns?

My app receives messages with a random number of bits at a random time. But two weeks ago I started to notice some almost regular patterns on the metrics of my app. I suspect they are some bots ...
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4answers
3k views

One-class classifier for time series data classification

My problem is different from the common time series data problem. What I need to do is check if future time series data is in accord with previous time series data I already consider to be correct. ...
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3answers
2k views

Predicting next action to take to reach a final state

Does anyone know of an algorithm that could be used to determine the next action to take to reach a desired state when trained on time-series data? For example, a robot starts at a certain state, ...
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1answer
269 views

How should I process music play data

I have music play data organized by the day on which each track was played, from March 1st, 2015 to August 30th, 2015. The data set contains count data for every day a song was played. I'd like to ...
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594 views

Is there any ability to use two ore more inputs for Elman recurrent neural network?

I have a problem with using neurolab python library: I'm trying to predict some time-series with help of Elman recurrent neural network: ...
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1answer
2k views

Anomaly detection in Time Series Data - Help Required [closed]

I am looking for algorithms on Anomaly detection for time series data. It is uni-variate analysis, considering single parameter (inlet pressure) of air compressor sensor data. The objective is to ...
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1answer
880 views

GE Predix's machine learning (anomaly detection) capabilities

Background: I am investigating time-series anomaly detection for industrial machine data, and have stumbled upon GE Predix. It seems like a promising tool, however, I am not familiar with their ...
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1answer
497 views

Time series_Calculation of monthly rolling average

How do we calculate monthly rolling average? I have monthly 2 years of data . I know that if it is 2 months rolling average ,we need to take the average of every 2 months . But since I need monthly ...
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1answer
226 views

Classification on time series data

Context: I am working on a classification project. where I recommend items to customers based on their past purchase history. Question: How will "time leakage" affect training? Example: Let's say ...
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1answer
553 views

In Orange, is it possible to analyze or visualize real time, streaming data?

Using orange, I would like to be able to do real time analysis or visualizations on streaming data. I would appreciate any input on the matter!
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84 views

binary longitudinal time series

What kind of feature engineering techniques should one apply for longitudinal data comprising of individual binary time interval data about when an activity was done during the day(we have this data ...
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77 views

Organic vs Paid Attribution Model

I'm wondering if there is literature or studies done on how to model organic attribution from paid user acquisition. So the context is, on our mobile app, we have paid installs that we purchase and ...
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58 views

Detect unusal slope increasing

I have a response variable series which will be generated randomly in a fixed interval [0-100] base on every second, and I want to detect the event when the new generated data is significantly greater ...
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1answer
358 views

Clustering efficiency in a discrete time-series

Is it possible to identify the point in time where the cluster separation is at its most in a discrete time series clustering? Say I have 4 clusters of discrete time series and I want to pick a ...
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3answers
2k views

How to best forecast simple binary data? [closed]

I have a set of timeseries binary (boolean) data, with intervals of 1 day. Each day can either be 1 or 0 (true/false). What is the best way to forecast the next day/week's data based on the data I ...
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1answer
217 views

Underlying model for prediction using different prediction variables

I have time-series energy consumption data for a duration of one-month. The frequency of data is half-hourly. The features of dataset are temperature - temperature value at particular time instant ...
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1answer
2k views

Impulse Response Function - Negative Shocks on R

I have two questions on how to produce impulse responses using R (1) Impulse responses to a negative shock in the independent variable (money supply) (2) Impulse responses at 2 standard deviations ...
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1answer
141 views

Time Series - Prediction

I have time series for product usage over an year on daily basis. Product usage exhibits seasonality i.e. it usage increase/decreases by more than the normal usage during that time. When i get the ...
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2answers
202 views

How to determine if a company decision was successful or not?

I'm trying to figure out if a decision taken in a company (offering discounts for specific products) is successful or not. I have done some research and saw that A/B testing might be a way to do this ...
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1answer
84 views

time series plot

Can we draw time series plot with only month and year in R? I don't have date variable in my dataset. Dataset looks like this- ...
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2answers
2k views

online detection of plateaus in time series

I need to detect plateaus in time series data online. The data I am working with represents the magnitude of acceleration of a tri-axis accelerometer. I want to find a reference time window that I can ...
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1answer
132 views

Predicting most likely application to be opened

Background I'm currently preparing for a paper in which I will discuss the ability to predict the most likely application to be opened by the user at the given time. The application will collect ...
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0answers
493 views

Predicting purchase order?

What is the best option or rather options to predict how much order a customer will place in the future, say next 3 months on a monthly basis. Also will a customer place an order. I used ARIMA to ...
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0answers
88 views

Trend Decline Graph Normalization

I am working on a project that should predict Alarm based on the input data. I am trying to use a supervised learning algorithm. But I do not have the exact target value based on the input for feeding ...
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2answers
2k views

Analyze performance Poisson regression model on a time series(count forecasting)

I have tried to build a model to forecast the count of a particular variable.The model that was used for the purpose was poisson .Unfortunately ,i don't have enough stat knowledge to analyze the model ...
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0answers
211 views

Machine learning on data with only time stamps

I'm working on trying to predict physical traffic volume over a network of intersections. The data I have is sorted per intersection and consists of the time (in sec after epoch) they passed and the ...
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0answers
58 views

local regression with streaming data

From a data stream i'm receiving a pair of measurements consisting of a current consumption and a current percentage every second. By accumulating the consumption over time it will represent ...
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72 views

What are standard ways to normalize lengths for multiple time series?

An example of some time series input I have in mind. Suppose I have multiple users working on a 20-minute search task, using a commercial search engine like Google, Yahoo, or Bing. It's the same task, ...
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1answer
7k views

Markov switching models

What are some reference sources for understanding Markov switching models?
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114 views

Interpretation of level, trend and seasonal indices in holt winters exponential smoothing

I am trying to learn Holt Winters exponential smoothing. In the algorithm there are three indices involved (level, trend, seasonality) while forecasting. My questions: ...
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1answer
762 views

ARIMAX v. ARX Time Series Modeling

I need to build a time series model with explanatory variables, and ARIMAX seems to be the one that comes up most frequently in practice, based on my survey of related work. I know ARX solves a ...
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1answer
250 views

Estimating the battery capacity using current power consumption and battery percentage

I want to estimate the current maximum capacity (in kWh) having the current power consumption (in kWh) and the state of charge of the battery (in %) available in a time series. I do not have a full ...
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614 views

Trajectory data mining and pattern recognition using ORB-SLAM and KNN-DTW

I've started working on a project about the trajectory data mining from videos - for example: snowboarding video from GoPro action camera. This is the continuation of my previous experiment (MotionML)...
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1answer
2k views

Decompose annual time series in R

I have a time series. Data points are available for each year from 1966 to 2000. Using R, I want to decompose this time series into trend, seasonal and random components. When I run the decompose ...
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3answers
1k views

How to predict an approximate weekly/monthly number, when the Unique Daily Visitors for that week/month are already known

I am trying to come up with a formula or machine learning algorithm using which I can approximately predict the weekly or monthly users. What to keep in mind is that I already have counts for the ...
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2answers
257 views

Time series data: How I measure influence of new product sales on existing product sales (statistically)?

Here my goal is… Find Product 5 (New Product) is really influencing other product sales (product 1 to 4) or not? If it is influencing other product sales, how much? New to R and tried several ...
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1answer
3k views

ARIMAX with spark-timeseries

Cloudera recently added the spark-time series library to github. According to the user docs, it definitely can fit autoregressive integrated moving average (ARIMA) models, but I see no mention of ...
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1answer
97 views

Please list some well tested api's for arima model

I am looking for a good python api for timeseries models such as ARIMA. Please list some well tested apis and few more advance models possible for financial time-series analysis.
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1answer
643 views

Classify Customers based on 2 features AND a Time series of events

I need help on what should be my next step in an algorithm I am designing. Due to NDAs, I can't disclose much, but I'll try to be generic and understandable. Basically, after several steps in the ...
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1answer
1k views

Combining Linear Regression and Time Series

Does anyone know of a predictive model that can combine the linear regression model and time series model? I have some data about some products. The data has two parts, some attributes about the ...
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0answers
68 views

What's the most robust way to predict the value of some noisy time series data?

I have some time series data (time, value) such as: ...
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2answers
821 views

Events prediction with time series of continuous variables as features

We have the feeling that behavior of a device in terms of continuous variables (fans speeds, temperatures, voltages, ...) has influence on rare events happening (components failures). I now have to ...