Questions tagged [time]
The time tag has no usage guidance.
30
questions
1
vote
1
answer
43
views
Dealing with varying predictive horizon
I know that the predictive horizon is the time window that runs from the observation of the data to the manifestation of the target variable.
But how can I deal with prediction if the time horizon ...
0
votes
0
answers
10
views
Predicting Year-End Outcome from Monthly (and Annual) Data
I have data on customers' usage of various product features over time. Each month, a customer can choose to use a feature or not.
I want to create a live system that produces the probability of a user ...
0
votes
0
answers
18
views
Given a 4d tensor for time series predicition
I have multiple time series datasets, which i want to train to an lstm model.
The shape of the training data is (735,2,5,4). 735 are the time steps, 2 are the two time Series datasets, 5 are the ...
0
votes
1
answer
20
views
Integrating time context in a machine learning model
Basically, what I'm curious about, are there any methods in machine learning to make the model take into account events that happen in real time that affect the data points during that time period. ...
0
votes
1
answer
61
views
What is exactly the input to a second lstm layer?
I am often confused about the lstm with more than one layer.
Imagine i have two lstm layer with 3 cells each layer.
What is exactly the input to the second lstm layer ?
0
votes
1
answer
39
views
Day number as a feature in Linear regression
Goal - To train a Linear regression model for climatic studies.
Planned features: - Temperatures, Latitude, Longitude, Day Number (1st February = 32)
Would it be correct to include day number like ...
0
votes
0
answers
26
views
Data stock pricing Python, unsuported string error
I have the data of stock prices and I reduced it to a smaller data set.
...
1
vote
1
answer
29
views
Detect data (web textual content) age
This is a broad question and maybe does not have an answer but I will try.
I have been thinking of some techniques to detect the date of publication of public data in the wild of the internet. Without ...
1
vote
0
answers
127
views
predict next purchase time of an item
I have a bunch of timestamps (purchase date from history), that looks like:
[1658753101, 1658760061, 1658824861, 1658846461, 1658853961, etc]
What I want is to based on that list predict next item ...
0
votes
0
answers
19
views
Stimulate real time data
I had historical data collected by sensors and would like to create a web interface project where users could observe the life-stream analytics displayed on it. May I know which specific platform (ex: ...
0
votes
1
answer
42
views
Why there is a gap when generating lags in time series?
I just started heading into time series forecasting, and a friend of mine who is doing this for several years showed me one of his projects. In his project, he was forecasting monthly sales quantity ...
0
votes
0
answers
66
views
Convert minute duration (string) to float
I am trying to convert my time watched in a netflix show to a float so I can total it up. I cannot figure out how to convert it. I have tried many ways, including:
...
0
votes
1
answer
355
views
parallel work on KNN in python
I have a question, related to parallel work on python
How I can use Processers =1,2,3... on k nearest neighbor algorithm when K=1, 2, 3,.. to find the change in time spent, speedup, and efficiency.
...
1
vote
0
answers
97
views
Handling date and time fields for classification task
I'm working on a classification task(The dataset is 400,000 rows and 30 columns) and one of my features was date-time. I've extracted the month, day of the week, and hour from the dataset (year is a ...
1
vote
3
answers
2k
views
Add timestamp as a feature to model
I am working with time-series data and am interested in adding time-stamp data (as a feature) into the (DNN) model. From the things I have read online so far, my only option is to come up with my own ...
1
vote
0
answers
48
views
Deep Learning with Time Series Data (containing Log Returns)
I am curious about how I would begin to approach this problem. I am working with a time series multi-indexed data frame (consisting of precomputed log returns) of various stocks. In this dataframe, ...
3
votes
2
answers
843
views
Which is meant by +/-9.2e18 years in timespan?
I was able to convert the 9.2e18 AD to a date, but I am confused about the exact date. Which date is 9.2e18 AD and and 9.2e18 BC?
Time span (absolute) - [9.2e18 BC, 9.2e18 AD] i.e +/- 9.2e18 years
...
2
votes
1
answer
66
views
Survival analysis to estimate kanban tasks completion times
I am working on a problem to estimate task completion time in kanban (project management tool).
While doing EDA, I looked at tasks that are either done or cancelled. In this case, I defined the ...
0
votes
1
answer
21
views
What is best practice to feature engineer from prior event counts?
Say for example I am building a model to predict a customer churn event from Spotify, with my target being whether a customer churns in the next 90 days.
One feature I might expect could be predictive ...
1
vote
0
answers
83
views
Modeling count data with time-dependent rate
For processes of discrete events occurring in continuous time with time-independent rate, we can use count models like Poisson or Negative Binomial. For discrete events that can occur once per sample ...
3
votes
1
answer
76
views
LSTM for time series forcasting
I manipulate the time series using the different structures of the neural networks in order to make a prediction, and I wonder if there is a way to choose the parameters of the networks intelligently? ...
1
vote
1
answer
2k
views
Date and time extraction from Excel file in Python or Pandas
I have an Excel file with a column that contain both date and time in a single cells as follows:
2020-07-10T13:32:01+00:00
I'm wondering how to extract this cell, split date and time (that are ...
1
vote
1
answer
76
views
Appropriate Machine Learning algorithm for modeling clustered time-varying binary outcome
I'll just dive right in. I have a decent-size (100K observations) dataset of time-varying continuous and categorical predictors. Categorical predictors, actually, usually do not change, however, ...
1
vote
1
answer
929
views
Get the average time between first and 2nd call (postgresql)
I have the following data in table where I want to calculate the average time between 1st and 2nd call.
I know how to get the average, but I have a though time to figure out how to subtract the 2nd ...
1
vote
1
answer
2k
views
Help improving my "read_excel" execution time in python. My code reads slowly
My first question here so please bare with me.
I'm trying to feed my neural network with training data read in from an excel file. It works perfectly fine when i have less than 50 rows in the sheet. ...
1
vote
0
answers
12
views
Standard(s) for data representing measurement times with their interval of validity?
Is there a standard for representing the time interval of a measurement?
Any actual measurement is made at a point in time with, perhaps, an interval over which it is considered valid. For example, ...
1
vote
2
answers
51
views
Classification with feature not available at time of model creation
I have problem statement to predict the probability of solving a task depending on multiple features for e.g. when the task was created, the time needed to work on a task, etc Please find a dummy ...
2
votes
1
answer
177
views
In survival analysis, which is the correct way to introduce a variable which changes the survival rate but occurs at different times?
I am making a survival analysis with a cox regression with proportional hazards, we want to analyze wheter the introduction of a phenomenon influences the time until the death of an individual.
A ...
1
vote
1
answer
52k
views
'list' object has no attribute 'values' when we are using append in python
Here I have a dataset with three inputs. Here I generated y value using append. After the append I got the output like this:
y.append(rec.iloc[0]['y'])
Then I ...
1
vote
0
answers
235
views
Linear correlation and XGboost regression for time series
I am working with sales time-series data, I have a history of 9 years of monthly data. I am trying to forecast sales for the next 12 months. I am using XGboost regression to build multivariate time ...