Good and Bad classification of CAKE

Published: 27 August 2024| Version 1 | DOI: 10.17632/8gpzcny5t4.1
Contributors:
Suraj Mondal, Tanmay Sarkar

Description

Data Description for Good and Bad Classification of Cake The dataset used for this project comprises 1,000 samples of cakes, split evenly between two categories: Good and Bad cakes. The primary goal is to classify a given cake sample as either Good or Bad based on a variety of attributes. Data Structure: Total Samples: 1,000 Good Cakes: 500 Bad Cakes: 500 Each sample in the dataset is represented by a set of features that capture different physical, chemical, and sensory properties of the cakes. The dataset includes a mix of numerical and categorical variables that help in differentiating between good and bad quality cakes. Below is a summary of the key features included: Features: Appearance: Colour: Categorical variable indicating the external colour of the cake (e.g., Golden, Dark, Pale). Surface Texture: Categorical variable representing the texture of the cake's surface (e.g., Smooth, Cracked, Rough). Moisture Content: Numerical variable (percentage) indicating the moisture content of the cake. This affects the cake's softness and freshness. Weight: Numerical variable representing the weight of the cake in grams. A deviation from the expected weight could indicate quality issues. pH Level: Numerical variable representing the pH level of the cake, which influences its taste and shelf life. Ingredient Proportion: Numerical variables indicating the proportions of key ingredients such as flour, sugar, eggs, and fat. Incorrect proportions can result in poor quality cakes. Baking Time and Temperature: Numerical variables representing the baking time (minutes) and baking temperature (degrees Celsius). Over or under-baking can affect the cake's texture and quality. Texture Profile: Categorical variable based on texture profile analysis (e.g., Firmness, Crumbliness, Springiness). These characteristics are crucial in determining whether the cake is classified as Good or Bad. Flavour Intensity: Numerical variable (scale of 1-10) rating the flavour intensity of the cake. Bland or overpowering flavours could be indicators of poor quality. Aroma: Categorical variable indicating the strength of the cake's aroma (e.g., Strong, Mild, Faint). The aroma is a critical sensory feature for classification. Crumb Structure: Categorical variable describing the internal crumb structure of the cake (e.g., Fine, Coarse, Dense). A good cake typically has a fine, uniform crumb structure. Shelf Life Indicator: Binary variable indicating whether the cake is within its optimal shelf life (1 = Yes, 0 = No). Cakes past their shelf life are more likely to be classified as Bad. Sensory Panel Rating: Numerical variable (scale of 1-10) based on evaluations from a sensory panel. This rating is a comprehensive indicator of overall cake quality. Defects: Categorical variable listing specific defects observed in bad cakes (e.g., Soggy Bottom, Burnt Edges, Uneven Rise).

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Categories

Biological Classification, Characterization of Food

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