Good and Bad classification of CAKE

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).