Multiclass classification problems are those where a label must be predicted, but there are more than two labels that may…
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Failure of Classification Accuracy for Imbalanced Class Distributions
Classification accuracy is a metric that summarizes the performance of a classification model as the number of correct predictions divided…
Continue ReadingAccuracy Fallacy: The Media’s Coverage of AI Is Bogus
Spoiler: They cant. However, in the book, “The Bestseller Code: Anatomy of the Blockbuster Novel,” the authors claim theyve “written…
Continue ReadingInterpretation of Kappa Values
Interpretation of Kappa ValuesEvaluate the agreement level with conditionYingting Sherry ChenBlockedUnblockFollowFollowingJul 5The kappa statistic is frequently used to test interrater reliability.…
Continue ReadingHyper-Parameter Tuning and Model Selection, Like a Movie Star
Hyper-Parameter Tuning and Model Selection, Like a Movie StarCoding, analyzing, selecting, and tuning like you really know what you’re doing. Caleb NealeBlockedUnblockFollowFollowingJun…
Continue Reading1st Place Solution for Intel Scene Classification Challenge
1st Place Solution for Intel Scene Classification ChallengeHosted by Analytics VidhyaAfzal SayedBlockedUnblockFollowFollowingJun 2IntroductionProblemYou are provided with a dataset of ~25k…
Continue ReadingHow Twitter and Machine Learning (KDE + LDA) help to predict Crime?
He (Gerber) uses, in addition to KDE, topic modeling on these messages, in particular LDA. As a brief summary, LDA…
Continue ReadingLayman’s Introduction to KNN
Layman’s Introduction to KNNk-nearest neighbour algorithm is where most people begin when starting with machine learning. Rishi SidhuBlockedUnblockFollowFollowingMay 20Photo by timJ…
Continue ReadingWhy Measuring Accuracy Is Hard (and important!) Part 2
What if I use this split instead:The naive way might be just to shuffle your dataset randomly and split it…
Continue ReadingWhy measuring accuracy is hard (and very important)!
We find some acceptable point on the ROC curve, set the threshold to that point, and use these two new…
Continue ReadingExtremely Imbalanced data — Fraud detection
This is because we can predict all the isFraud=0 cases perfectly, but none of the isFraud=1 cases. So out of…
Continue ReadingReview: CRF-RNN — Conditional Random Fields as Recurrent Neural Networks (Semantic Segmentation)
Review: CRF-RNN — Conditional Random Fields as Recurrent Neural Networks (Semantic Segmentation)An Approach Integrating CRF into End-to-end Deep Learning SolutionSH TsangBlockedUnblockFollowFollowingMar 3In this…
Continue ReadingPython Data Science Getting Started Tutorial: NLTK
The combined classifier algorithm is a commonly used technique, which is implemented by creating a voting system. Each algorithm has…
Continue ReadingMachine learning with the “diabetes” data set in R
Machine learning with the “diabetes” data set in RClassification with KNN, logistic regression, and decision treesWilliam ButlerBlockedUnblockFollowFollowingJan 17Inspired by Susan Li’s article…
Continue ReadingLogistic Regression Model Tuning with scikit-learn — Part 1
Logistic Regression Model Tuning with scikit-learn — Part 1Comparison of metrics along the model tuning processFinn QiaoBlockedUnblockFollowFollowingJan 8Classifiers are a core component of machine…
Continue ReadingImpact of Dataset Size on Deep Learning Model Skill And Performance Estimates
We will define a model that performs well on this dataset as a model that has effectively learned the two…
Continue ReadingHow to Reduce the Variance of Deep Learning Models in Keras Using Model Averaging Ensembles
The model then has a single hidden layer with 15 modes and a rectified linear activation function, then an output…
Continue ReadingText Generation Using Recurrent Neural Networks
It has an average accuracy of 0.6245 and loss of 1.25 over 5 randomly sampled test sequences.Yes, but to talk…
Continue ReadingA Guide for Building Convolutional Neural Networks
Before that, you’re just experimenting and prototyping and so there’s no need to make your training time longer by having…
Continue ReadingHow I improved a Human Action Classifier to 80% Validation Accuracy in 6 Easy Steps
The ensemble achieved a validation accuracy of 0.821 which is a significant improvement from the baseline paper’s accuracy of 0.672.Background…
Continue ReadingHoly Grail of AI for Enterprise — Explainable AI
In reality, Customers are the less bothered accuracy of AI model, but their concerns are about Cluelessness of Data Scientist…
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