Textual Analysis

6.

Evaluation and Interpretation

6.1.

Classification Model Evaluation

6.1.1.

6.1.1.1.

6.1.1.2.

6.1.1.3.

6.1.1.4.

6.1.2.

Advanced Metrics

6.1.2.1.

Macro vs Micro Averaging

6.1.2.2.

Weighted Metrics

6.1.2.3.

Matthews Correlation Coefficient

6.1.3.

Visualization Tools

6.1.3.1.

Confusion Matrix

6.1.3.2.

6.1.3.3.

Precision-Recall Curve

6.1.3.4.

6.1.4.

Validation Strategies

6.1.4.1.

Cross-Validation Techniques

6.1.4.2.

Stratified Sampling

6.1.4.3.

Time Series Validation

6.2.

Regression Model Evaluation

6.2.1.

Mean Absolute Error

6.2.2.

Mean Squared Error

6.2.3.

Root Mean Squared Error

6.2.4.

6.3.

Clustering Evaluation

6.3.1.

Internal Validation Measures

6.3.1.1.

Silhouette Analysis

6.3.1.2.

Calinski-Harabasz Index

6.3.1.3.

Davies-Bouldin Index

6.3.2.

External Validation Measures

6.3.2.1.

Adjusted Rand Index

6.3.2.2.

Normalized Mutual Information

6.3.2.3.

Homogeneity and Completeness

6.4.

Topic Model Evaluation

6.4.1.

6.4.1.1.

Definition and Calculation

6.4.1.2.

Limitations of Perplexity

6.4.2.

Topic Coherence

6.4.2.1.

Coherence Measures

6.4.2.2.

Interpretability Assessment

6.4.3.

Human Evaluation

6.4.3.1.

Topic Quality Assessment

6.4.3.2.

Inter-Annotator Agreement

6.5.

Summarization Evaluation

6.5.1.

6.5.1.1.

6.5.1.2.

6.5.1.3.

6.5.2.

6.5.3.

Semantic Similarity Measures

6.5.3.1.

6.5.3.2.

6.5.4.

Human Evaluation Criteria

6.5.4.1.

Content Coverage

6.5.4.2.

Linguistic Quality

6.5.4.3.

Overall Responsiveness

6.6.

Model Interpretability

6.6.1.

Importance of Interpretability

6.6.1.1.

Trust and Transparency

6.6.1.2.

Regulatory Compliance

6.6.1.3.

6.6.2.

Local Interpretability Methods

6.6.2.1.

6.6.2.1.1.

Perturbation-Based Explanations

6.6.2.1.2.

Local Linear Approximation

6.6.2.2.

6.6.2.2.1.

6.6.2.2.2.

Additive Feature Attribution

6.6.3.

Global Interpretability Methods

6.6.3.1.

Feature Importance

6.6.3.2.

Partial Dependence Plots

6.6.3.3.

Model-Agnostic Methods

6.6.4.

Attention Visualization

6.6.4.1.

Attention Heatmaps

6.6.4.2.

Head-View Analysis

6.6.4.3.

Layer-Wise Analysis

6.7.

Data Visualization for Text

6.7.1.

Word-Level Visualizations

6.7.1.1.

6.7.1.2.

Frequency Distribution Plots

6.7.1.3.

N-gram Frequency Charts

6.7.2.

Document-Level Visualizations

6.7.2.1.

Document Similarity Heatmaps

6.7.2.2.

Clustering Visualizations

6.7.2.3.

Topic Distribution Plots

6.7.3.

Network Visualizations

6.7.3.1.

Co-occurrence Networks

6.7.3.2.

Entity Relationship Graphs

6.7.3.3.

Citation Networks

6.7.4.

Interactive Dashboards

6.7.4.1.

Topic Model Browsers

6.7.4.2.

Real-Time Analytics Dashboards

6.7.4.3.

Exploratory Data Analysis Tools

6.7.5.

Dimensionality Reduction Visualization

6.7.5.1.

6.7.5.2.

PCA Projections

6.7.5.3.

UMAP Visualizations

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