Implement plain KNN classifier and testing infrastructure

- Add plain KNN implementation with JSONL data processing
- Create Docker deployment setup with python:3.13-slim base
- Add comprehensive OJ-style testing system with accuracy validation
- Update README with detailed scoring mechanism explanation
- Add run.sh script following competition manual requirements

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

run.sh

@@ -0,0 +1,22 @@
+#!/bin/bash
+SCRIPT_DIR=$(dirname "$0")
+PARENT_DIR="$(dirname "$SCRIPT_DIR")"
+
+# 根据运行环境选择文件路径
+if [ "$ALIPAY_APP_ENV" = "prod" ]; then
+    PREDICTIONS_RESULT_FILE="/home/admin/workspace/job/output/predictions/predictions.jsonl"
+    DATASET_FILE="/home/admin/workspace/job/input/test.jsonl"
+else
+    PREDICTIONS_RESULT_FILE="${PARENT_DIR}/data/predictions.jsonl"
+    DATASET_FILE="${PARENT_DIR}/data/data.jsonl"
+fi
+
+echo $PREDICTIONS_RESULT_FILE
+
+#以上内容**不可**修改!
+#选手仅可修改下面的test为自己的实际比赛代码入口
+chmod +x "${SCRIPT_DIR}/test"
+
+"${SCRIPT_DIR}/test" \
+    --dataset "$DATASET_FILE" \
+    --predictions "$PREDICTIONS_RESULT_FILE"