Good and Bad classification of Simui

The dataset for the project on the classification of cooked Simui (a type of traditional dish) consists of 1,000 samples, divided into two categories: *500 good samples* and *500 bad samples*. This dataset aims to build a classification model capable of distinguishing between well-cooked and poorly-cooked Simui.

### *Dataset Overview:*

The samples in this dataset are based on specific characteristics of the cooked Simui, such as texture, appearance, flavor, and consistency. These qualities are commonly used by culinary experts to assess the quality of cooked Simui. The good and bad samples were carefully labeled based on sensory evaluations conducted by culinary specialists. Each sample was carefully selected to represent real-world scenarios of properly cooked versus poorly cooked Simui.

### *Class Labels:*
- *Good Simui (500 samples):* These are the samples that meet the required standards for a well-prepared Simui dish. They exhibit the right texture (neither too soft nor too dry), a pleasing appearance (uniform and smooth), and an appealing taste and aroma. The cooking method, timing, and ingredients contribute to the final quality of the dish.

- *Bad Simui (500 samples):* These samples represent cooked Simui that failed to meet the standards. Common characteristics of bad Simui include overcooked, undercooked, clumped, overly dry, too mushy, or having an unappetizing appearance. The dish may also have an undesirable taste, underseasoning, or improper consistency.

### *Features:*
The dataset includes a variety of features that contribute to the classification of good or bad Simui. These features may include:
1. *Texture:* The mouthfeel of Simui, categorized as soft, firm, or mushy.
2. *Appearance:* The visual quality, including color, shape, and consistency of the Simui strands.
3. *Aroma:* A descriptive analysis of the smell, where a fresh, pleasant aroma denotes good quality, while a burnt or sour smell represents a bad sample.
4. *Taste:* The flavor profile, including sweetness, saltiness, and seasoning balance. This is an important sensory aspect in distinguishing good from bad Simui.
5. *Moisture Content:* This feature measures the water content of the cooked Simui. Proper moisture level is crucial for the perfect texture.
6. *Clumping:* Whether the Simui strands remain separated or clump together in a sticky mass. Clumping is often a sign of overcooking or improper preparation.
7. *Cooking Time:* A feature to track how long the Simui was cooked. Cooking time directly influences the texture and consistency.

Each sample has been labeled according to a set of predefined quality criteria established by culinary experts, ensuring that the dataset is consistent and reliable.

本项目用于**熟制西米（Simui）**分类的数据集共包含1000个样本，分为两类：*优质样本500个*与*劣质样本500个*。本数据集旨在构建可区分合格与不合格熟制西米的分类模型。

### *数据集概览:*

本数据集的样本基于熟制西米的特定品质特征，包括质地、外观、风味与稠度。这些品质维度是烹饪专家评估熟制西米品质的通用标准。优质与劣质样本均由烹饪专家通过感官评价完成精准标注，且每个样本均经过精心挑选，以贴合真实场景下合格与不合格熟制西米的实际状态。

### *类别标签:*
- *优质西米（500个样本）:* 此类样本符合合格西米菜肴的制备标准，具备适宜的质地（既不过软也不过干）、均匀顺滑的美观外观，以及宜人的口感与香气。菜肴的最终品质受烹饪方法、时长与配料的共同影响。

- *劣质西米（500个样本）:* 此类样本代表未达品质标准的熟制西米。劣质西米的常见特征包括过煮、欠煮、结块、过度干燥、过于软烂，或外观缺乏吸引力。该类菜肴还可能存在口感不佳、调味不足或质地不合格的问题。

### *特征维度:*
本数据集包含多种可用于区分优质与劣质西米的特征，具体如下：
1. *质地（Texture）:* 西米的口感，可分为软糯、紧实或软烂三类。
2. *外观（Appearance）:* 视觉品质，涵盖西米条的色泽、形态与稠度。
3. *香气（Aroma）:* 气味描述分析，清新宜人的香气代表优质样本，而焦糊或酸败气味则对应劣质样本。
4. *口感（Taste）:* 风味特征，包括甜度、咸度与调味平衡度，是区分优质与劣质西米的重要感官维度。
5. *水分含量（Moisture Content）:* 用于衡量熟制西米的水分占比，适宜的水分含量是实现理想质地的关键。
6. *结块情况（Clumping）:* 西米条是否保持分散状态，或粘连形成黏团。结块通常是过煮或制备不当的标志。
7. *烹饪时长（Cooking Time）:* 记录西米的烹饪时长，该参数直接影响西米的质地与稠度。

所有样本均按照烹饪专家制定的预设品质准则完成标注，确保数据集具备一致性与可靠性。