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

Questions tagged [online-learning]

The tag has no usage guidance.

0
votes
0answers
21 views

Distinguishing Legitimate Anomalies From True Anomalies

In order to detect anomalous user commands, I am using a One Class SVM (OCSVM). First, I build a OCSVM model over normal commands of the user. Then, upon receiving a new command, the model either ...
0
votes
0answers
8 views

Securing elearning using data mining techniques

This is my first question here. I was given the topic above as my school project topic and I have no idea what that is. I need an explanation of what it means to secure elearning using data mining ...
0
votes
0answers
18 views

Stat-of-the-art Online Linear Regression alogirthms

I'm trying to find state-of-the-art linear regression algorithms for streaming datasets (online learning). However, I found only two algorithms so far, SGD regressor Passive Aggressive regression ...
0
votes
1answer
56 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 ...
0
votes
0answers
93 views

Train model on new class without retraining on old classes

I created a face recognition system in which we train model on person's face , what i want is to to train them on new person's face without retaining on old man face , is it possible. Please suggest ...
2
votes
1answer
62 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 ...
0
votes
1answer
35 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
vote
1answer
50 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 ...
0
votes
0answers
19 views

On-line learning with gradient descent doesn't work

I want to on-line learning of liner regression. [added] initial weights are [w1,w2,w3]=[1,1,1] input data is something like...(x1,x2,x3) ...
2
votes
0answers
98 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
vote
0answers
105 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
vote
1answer
77 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-...
0
votes
0answers
6 views

May online TD learner perform better in very non-stationary environments?

Consider these environment mappings: simple somewhat noisy and smoothly-trendy very noisy and sharply-trendy For the first two my realization of an experience-replay double Q-learning agent works ...
0
votes
1answer
130 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
votes
1answer
53 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}\...
3
votes
1answer
237 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 ...
2
votes
3answers
2k 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
votes
1answer
74 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
vote
1answer
331 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 ...
0
votes
0answers
78 views

Update model parameter with new data, discarding old data

I have this dataset, and I am using y = (a * x^n) / (b + x^n) Hill function as the model, where a is the limit of the Hill curve,...
1
vote
0answers
47 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
votes
1answer
1k 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
vote
2answers
79 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
votes
0answers
309 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
vote
0answers
173 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
votes
1answer
143 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,...
4
votes
2answers
366 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
vote
1answer
194 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 ...
4
votes
0answers
310 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
votes
2answers
225 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
votes
1answer
253 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 "...
1
vote
0answers
39 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 ...
3
votes
2answers
1k 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
vote
1answer
90 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
votes
1answer
107 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 ...
10
votes
1answer
4k 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 ...
9
votes
1answer
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/...