Questions tagged [online-learning]

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100 views

Incremental Learning with sklearn: warm_start, partial_fit(), fit()

I have built an ML model with the goal of making predictions for targets of the following week. In general, new data will come in and be processed at the end of each week and be in the same data ...
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0answers
16 views

Retaining past learning with Incremental Learning [closed]

I have built an ML model with the goal of making predictions for targets of the following week. In general, new data will come in and be processed at the end of each week and be in the same data ...
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0answers
9 views

Add new category/word to Keras embedding layer

I have a Keras model that is regularly updated by running a few additional epochs on new data once it becomes available. Part of the model is an embedding layer for a categorical feature. Recently ...
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1answer
60 views

What is the difference between continual learning and active learning?

As per my understanding, active learning is a kind of continual learning. Is there any difference between them?
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1answer
29 views

Incremental modelling of kmeans in pyspark

I have a large dataset and trained the model with kmeans for the first time. I saved the model and pipeline used . Now again I started collecting data. After sufficient data is collected using old ...
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1answer
49 views

SGDClassifier partial_fit() for online learning - is one step of gradient descent enough?

I'm interested in incremental (online) learning for my logistic regression model trained with SGDClassifier. Basically updating the model as more labeled data comes ...
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0answers
31 views

Continous Learning and Shifting Patterns

I've been intensively studying neural networks which try to predict a vector based on a given input matrix. The input matrix is a N x H matrix and the output vector a N x 1 vector. The network is ...
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0answers
23 views

Changing data structure in incremental learning of LSTM

This is a question which may or may not have open-ended answers. I am curious what you think and hoping to get a starting point. I am wondering what we do if we have a categorical variable in the set, ...
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0answers
20 views

Understanding experiments in Continual Learning

Via paper Continual Learning Through Synaptic Intelligence, I see this figure for Split MNIST benchmark, but there is a point I can get. Here there are 5 tasks, ...
2
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1answer
137 views

Distinguish Multi-Task vs Single-incremental Task in Continual Learning

I read through the Internet and found this: Most of Continuous Learning studies focus on a Multi-Task scenario, where the same model is required to learn incrementally a number of isolated tasks ...
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1answer
43 views

In Incremental Learning will the model be updated automatically?

I came across Incremental Learning algorithms paper, where incremental algorithms are compared. I have problem with general understanding. Will the model be updated /adapts itself automatically when ...
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4answers
663 views

SGDClassifier: Online Learning/partial_fit with a previously unknown label

My training set contains about 50k entries with which I do an initial learning. On a weekly basis, ~ 5k entries are added; but the same amount "disappears" (as it is user data which has to be deleted ...
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0answers
307 views

SGDClassifier accuracy MUCH worse than LinearSVC

with LinearSVC, I get an accuracy off 0.89: ...
1
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0answers
41 views

What strategies and algorithms are suited for using the time wasted in collecting big data?

Most state of art algorithms right now is using/exploiting big data. My concern is what can you do to maximize reward while waiting for large amount of data that you think is appropriate. For ...
2
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0answers
256 views

Comparison between approaches for timeseries anomaly detection

After various days of research, I could take a global picture of the existing methods to perform anomaly detection on time series, namely: Forecasting with Deep Learning. Eg. RADM or LSTM model ...
1
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0answers
235 views

Forecasting vs non-forecasting predition for time series anomaly detection

I have got the objective of implementing a uni/multivariate online anomaly detection system. After multiple days of research, I could collect many ways to achieve this (Eg. moving average solutions ...
1
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0answers
10 views

What is the effect of the use of online-learning algorithms on non steaming data?

am wondering what the effects of using a passive-aggressive classifier instead of something like a SVM classifier on a non-streaming data would be. In other words, what are the general assumptions ...
0
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1answer
590 views

First order vs Second order online machine learning algorithms

In this git repo the online learning algorithms are classified as first order and second order. I tried searching what it means, yet I'm unable to understand the different between such first oder and ...
2
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1answer
64 views

Work experience in Data Science: Couple hours with A-level student [closed]

Our company has accepted an A-level student (18-year old, just before uni) for some work experience. The student will be with me for a couple of hours. I do data analysis and I'm quite busy at the ...
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1answer
63 views

Predicting crowd density using real time streaming data

I would like to make predictions about how crowded a location (postal code mapped to lat/lng coords) would be. I would like to provide predictions to questions like: what’s the crowd density going to ...
1
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1answer
63 views

Should I update my regularisation L1 and L2 regularisation parameters in online setting?

I have been working on online learning for a few weeks now, especially with Vowpal Wabbit and logistic regression. My understanding of the online learning algorithms and the problem is alright but I ...
5
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2answers
304 views

How to continue incremental learning when a categorical variable has been assigned additional category labels?

Please help answer this question or point me to any resource. There is a model in an environment where training happens with new data and the data is discarded after training is completed. This keeps ...
1
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0answers
183 views

Online vs minibatch training for speed

If I do online learning in a setting where I have a HUGE amount of data, is that faster than doing minibatch learning (even if I optimize my batch size for GPU use, that is, use a multiple of 32 ...
1
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1answer
172 views

Clarifying my understanding of on-policy RL (online SARSA)

I want to clarify I have understood how SARSA works in nuances. Consider an original definition taken from ON-LINE Q-LEARNING USING CONNECTIONIST SYSTEMS. G. A. Rummery & M. Niranjan. CUED/F-...
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1answer
368 views

contextual bandits for online learning

Which of the algorithms in the current literature for contextual bandits can be implemented for online learning and which ones can't? I'd really appreciate it if someone could provide a link to papers ...
2
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1answer
112 views

Reasoning for temporal difference update rule

In TD(0) learning where the value function is given by $V(s) = w^T\phi(s)$ where $w$ is a weight vector and $\phi$ is a feature map, the weight update is given by $w_{t+1} = w_{t} + \eta\delta_{t+1}\...
2
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1answer
435 views

Testing Multi-Arm Bandits on Historical Data

Suppose I want to test a multi-arm bandit algorithm in the contextual setting on a set of historical data. For simplicity, let's assume there are only two arms A and B and suppose the rewards are ...
3
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3answers
5k views

How to retrain the neural network when new data comes in?

I am new to deep learning. Can anybody help me with the online learning implimentation for deep learning models. As per my understanding, i can save a keras/tensorflow model after training and when ...
0
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1answer
172 views

Recommend tags for documents

I'm working on a unusual issue (for me) and I need some advice. My goal is to have a recommendation algorithm that propose tags for a document, based on all the previously tagged documents. For ...
1
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1answer
609 views

how to retrain model with periodic new features?

I've trained a gradient boosting classification model. But, suppose i've a set of fixed features F1,F2....Fn and new features which are added weekly (no. of actions done in that week). So, after 2 ...
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0answers
55 views

How to calculate inverse of square matrix for streaming or online data as all data are not available at once?

Suppose initial data is $D$ and need to calculate the inverse of covariance of matrix $D$ i.e. $C = cov(D,D)$, where $cov$ represents covariance. $B = inv(C)$ Now, new data $N$ appears. So matrix D ...
2
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1answer
4k views

Real time noise removal using Savitzky-Golay Method

I would like to ask if Savitzky-Golay can be implemented on real-time data. I have used it on a fixed array size, but would like to extend it to output values for real-time sensor data. Can anyone ...
1
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2answers
105 views

Online learning w/ feature weighting/adjusting

Let's say I have a supervised learning problem with a sequence of features and labels. First, I learn on the training data and then I decide to stream in data, point by point and do online learning. ...
2
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0answers
422 views

How do I train a contextual bandit policy?

Say I'm attempting to improve click-through rates on videos on my website. I've been reading the literature on contextual bandits and came across the Microsoft MWT white paper. I believe this is the ...
1
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0answers
265 views

Online methods for sequence prediction

A ml beginner here, so please bear with me. If I understand correctly RNNs seem to be the go to method right now for sequence prediction for a given input (single/as a sequence). But I do not have ...
2
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1answer
163 views

Finding a proper method for an online driving style classification using acceleration data

I am using a smartphone in my car to gather acceleration data (both longitudinal and lateral). Now, I want to classify my data in real-time based on the acceleration force applied through accelerating,...
5
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2answers
1k 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 ...
1
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1answer
330 views

Can FTRL be applied on linear least squares? or is it just for logistic regression models?

I'm exploring follow-the-regularized-leader FTRL proximal gradient descent: paper, reference implementation. Everywhere FTRL is mentioned, the loss surface for the gradient decent is the ...
5
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0answers
451 views

differences between LSQR and FTRL when working with very sparse data

I have a 2M instances dataset with millions of very very sparse dummy variables created using the hashing trick = ...
4
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2answers
256 views

is neural networks an online algorithm by nature?

I have been doing machine learning for a while, but bits and pieces come together even after some time of practicing. In neural networks, you adjust the weights by doing one pass (forward pass), and ...
3
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1answer
337 views

Online/incremental unsupervised dimensionality reduction for use with classification for event prediction

Consider the application: We have a set of users and items. Users can perform different action types (think browsing, clicking, upvoting etc.) on different items. Users and items accumulate a "...
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0answers
47 views

Parameters for OnlineLogisticRegression function in Mahout

Can anyone tell me where do I find any documentation for parameters like: -stepOffset -alpha -decayExponent in an OnlineLogisticRegression function in ...
6
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2answers
3k views

Is there a difference between on-line learning, incremental learning and sequential learning?

What I mean is the following: Instead of processing all the training data at once and calculating a model, we process one data point at a time and update the model directly afterwards. I have seen ...
1
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1answer
108 views

Assigning new items to existing similarity based clustering

Given some clusters created from similarity measures between items, is there a recommended way to assign a new item to an existing cluster based on similarity alone? (i.e. avoiding re-clustering) ...
2
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1answer
138 views

Linear combination of weak estimators over fuzzy classifiers?

Having: a set of soft fuzzy classifiers (classification onto overlapping sets) $C_i(x) \to [0,1]$; a corresponding set of weak estimators $R_i(z)$ of the form $R_i(z) = \mathit{EX}(y\mid z)$. The ...
13
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1answer
5k views

On-line random forests by adding more single Decisions Trees

A Random Forest (RF) is created by an ensemble of Decision Trees's (DT). By using bagging, each DT is trained in a different data subset. Hence, is there any way of implementing an on-line random ...
10
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2answers
3k views

Libraries for Online Machine Learning

I am looking for packages (either in python, R, or a standalone package) to perform online learning to predict stock data. I have found and read about Vowpal Wabbit (https://github.com/JohnLangford/...