Articles About Machine Learning

How To Estimate A Baseline Performance For Your Machine Learning Models in Weka

Last Updated on December 13, 2019 It is really important to have a performance baseline on your machine learning problem. It will give you a point of reference to which you can compare all other models that you construct. In this post you will discover how to develop a baseline of performance for a machine learning problem using Weka. After reading this post you will know: The importance in establishing a baseline of performance for your machine learning problem. How […]

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Time Series Prediction with LSTM Recurrent Neural Networks in Python with Keras

Last Updated on August 28, 2020 Time series prediction problems are a difficult type of predictive modeling problem. Unlike regression predictive modeling, time series also adds the complexity of a sequence dependence among the input variables. A powerful type of neural network designed to handle sequence dependence is called recurrent neural networks. The Long Short-Term Memory network or LSTM network is a type of recurrent neural network used in deep learning because very large architectures can be successfully trained. In […]

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How To Use Regression Machine Learning Algorithms in Weka

Last Updated on August 22, 2019 Weka has a large number of regression algorithms available on the platform. The large number of machine learning algorithms supported by Weka is one of the biggest benefits of using the platform. In this post you will discover how to use top regression machine learning algorithms in Weka. After reading this post you will know: About 5 top regression algorithms supported by Weka. How to use regression machine learning algorithms for predictive modeling in […]

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How To Use Classification Machine Learning Algorithms in Weka

Last Updated on August 22, 2019 Weka makesĀ a large number of classification algorithms available. The large number of machine learning algorithms available is one of the benefits of using the Weka platform to work through your machine learning problems. In this post you will discover how to use 5 top machine learning algorithms in Weka. After reading this post you will know: About 5 top machine learning algorithms that you can use on your classification problems. How to use 5 […]

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Sequence Classification with LSTM Recurrent Neural Networks in Python with Keras

Last Updated on September 3, 2020 Sequence classification is a predictive modeling problem where you have some sequence of inputs over space or time and the task is to predict a category for the sequence. What makes this problem difficult is that the sequences can vary in length, be comprised of a very large vocabulary of input symbols and may require the model to learn the long-term context or dependencies between symbols in the input sequence. In this post, you […]

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How to Use Ensemble Machine Learning Algorithms in Weka

Last Updated on August 22, 2019 Ensemble algorithms are a powerful class of machine learning algorithm that combine the predictions from multiple models. A benefit of using Weka for applied machine learning is that makes available so many different ensemble machine learning algorithms. In this post you will discover the how to use ensemble machine learning algorithms in Weka. After reading this post you will know: About 5 top ensemble machine learning algorithms. How to use top ensemble algorithms in […]

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Understanding Stateful LSTM Recurrent Neural Networks in Python with Keras

Last Updated on August 27, 2020 A powerful and popular recurrent neural network is the long short-term model network or LSTM. It is widely used because the architecture overcomes the vanishing and exposing gradient problem that plagues all recurrent neural networks, allowing very large and very deep networks to be created. Like other recurrent neural networks, LSTM networks maintain state, and the specifics of how this is implemented in Keras framework can be confusing. In this post you will discover […]

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How To Compare the Performance of Machine Learning Algorithms in Weka

Last Updated on December 11, 2019 What algorithm should you use for a given machine learning problem? This is the challenge of applied machine learning. There is no quick answer to this question, but there is a reliable process that you can use. In this post you will discover how to find good and even best machine learning algorithms for a data set by directly comparing them in Weka. After reading this post you will know: The process for discovering […]

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How to Tune Machine Learning Algorithms in Weka

Last Updated on December 11, 2019 You can get the most from a machine learning algorithm by tuning its parameters, called hyperparameters. In this post you will discover how to tune machine learning algorithms with controlled experiments in Weka. After reading this post you will know: The importance of improving the performance of machine learning models by algorithm tuning. How to design a controlled experiment to tune the hyperparameters of a machine learning algorithm. How to interpret the results from […]

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Data Leakage in Machine Learning

Last Updated on August 15, 2020 Data leakage is a big problem in machine learning when developing predictive models. Data leakage is when information from outside the training dataset is used to create the model. In this post you will discover the problem of data leakage in predictive modeling. After reading this post you will know: What is data leakage is in predictive modeling. Signs of data leakage and why it is a problem. Tips and tricks that you can […]

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