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Uncertainty in Multiclass Classification

Dr. Rishabh Pathak
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 ...
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What is Biostatistics?

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Dr. Rishabh Pathak


Biostatistics is a specialized branch of statistics that focuses on the design, analysis, and interpretation of data in the fields of biology, medicine, public health, and related disciplines. It involves the application of statistical methods to biological and health-related research to address questions related to disease prevention, treatment effectiveness, epidemiology, genetics, and other areas of study.

The key aspects of biostatistics include:


1.  Study Design: Biostatisticians play a crucial role in designing research studies and clinical trials by determining sample sizes, selecting appropriate study designs, and developing protocols to ensure the validity and reliability of the results.

2. Data Analysis: Biostatistical methods are used to analyze data collected from experiments, observational studies, surveys, and clinical trials. This includes the use of techniques such as regression analysis, survival analysis, meta-analysis, and Bayesian statistics to draw meaningful conclusions from complex datasets.

3.  Epidemiology: Biostatistics is closely linked to epidemiology, the study of the distribution and determinants of diseases in populations. Biostatistical methods are used to analyze disease patterns, risk factors, and trends in public health research to inform disease prevention and control strategies.

4.   Genetics and Genomics: In the field of genetics and genomics, biostatistics is used to analyze genetic data, identify genetic markers associated with diseases, and study patterns of inheritance. Techniques such as linkage analysis, association studies, and genome-wide association studies are commonly employed in genetic research.

5.  Public Health: Biostatistics plays a vital role in public health research by analyzing health outcomes, assessing the impact of interventions, and evaluating health policies and programs. It helps public health professionals make evidence-based decisions to improve population health and well-being.


Overall, biostatistics is an essential tool for researchers, healthcare professionals, and policymakers in the biological and health sciences to analyze data, draw meaningful conclusions, and make informed decisions based on empirical evidence. By applying statistical methods to biological and health-related research, biostatistics contributes to advancements in medical science, public health practice, and the understanding of complex biological processes.

 

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