1. What is Uncertainty in Classification? Uncertainty refers to the model’s confidence or doubt in its predictions. Quantifying uncertainty is important to understand how reliable each prediction is. In multiclass classification , uncertainty estimates provide probabilities over multiple classes, reflecting how sure the model is about each possible class. 2. Methods to Estimate Uncertainty in Multiclass Classification Most multiclass classifiers provide methods such as: predict_proba: Returns a probability distribution across all classes. decision_function: Returns scores or margins for each class (sometimes called raw or uncalibrated confidence scores). The probability distribution from predict_proba captures the uncertainty by assigning a probability to each class. 3. Shape and Interpretation of predict_proba in Multiclass Output shape: (n_samples, n_classes) Each row corresponds to the probabilities of ...
Epileptiform bursts are a specific EEG pattern characterized by a series of rapid, repetitive spikes or sharp waves that indicate abnormal electrical activity in the brain, typically associated with seizure activity. 1. Definition : o Epileptiform bursts consist of brief, high-frequency discharges that can appear as spikes or sharp waves. These bursts are indicative of underlying epileptic activity and can occur in various seizure types. 2. EEG Characteristics : o The bursts are often more monomorphic and stereotyped compared to non-epileptic bursts, exhibiting greater rhythmicity, especially in the faster frequency ranges. This distinct waveform helps differentiate them from other types of EEG activity, such as those seen in non-epileptic conditions. o Epileptiform bursts can vary in duration and frequency, and they may evolve into more complex patterns, such as ge...