异常检测新

【文件属性】：
文件名称：异常检测新
文件大小：1.61MB
文件格式：ZIP
更新时间：2021-02-25 11:05:39
JupyterNotebook 异常检测 使用Z分数和TQR检测异常 使用Z分数 i> finding mean and standard deviation of the dataset ii> finding Z score, Z = (X-u)/sigma iii> values for which Z > Threshold are outliers 使用IQR：- i> interquantile range works on percentile ii> sort the data in increasing order iii> let 25 and 75 percentile values be x and y respectively iv> finding IQR = y-x ii> values not in the range (x-1.5*IQR,y+1.5*I

【文件预览】：
Anomaly_Detection_new-master
----anomaly_detection_model_final.tflite(4KB)
----OBD_sensors_new_test.csv(152KB)
----New_way_data _base.csv(592KB)
----OBD_4_sensors.csv(2.01MB)
----anomaly_model.h5(73KB)
----Regression_model_2.sav(1KB)
----anomaly_in_4_sensors_model.tflite(4KB)
----Anomaly_detection_in_each_sensor.ipynb(58KB)
----anomaly_detection_model_final_2.h5(53KB)
----anomaly_in_4_sensors_model.h5(51KB)
----Regression_model.sav(1KB)
----OBD_sensors_new.csv(314KB)
----scalar_values_2.sav(612B)
----converted_model.tflite(4KB)
----model.h5(43KB)
----Anomaly using NN-2.ipynb(54KB)
----dataset_OBD_new.csv(179KB)
----Anamoly Detection.ipynb(129KB)
----Loading the model.ipynb(2KB)
----Regression_model.ipynb(4KB)
----.ipynb_checkpoints()
--------Regression_model-checkpoint.ipynb(4KB)
--------Regression_model_2-checkpoint.ipynb(6KB)
--------Anomaly_using_NN_new_improved-checkpoint.ipynb(67KB)
--------Anomaly using NN-2-checkpoint.ipynb(64KB)
--------Anamoly Detection-checkpoint.ipynb(129KB)
--------Anomaly_detection_in_each_sensor-checkpoint.ipynb(58KB)
----README.md(659B)
----Finding outliers using thresholding.ipynb(5KB)
----Regression_model_2.ipynb(6KB)
----Anomaly using NN.ipynb(88KB)
----OBD_4_sensors_2.csv(1.87MB)
----anomaly_model_new.h5(50KB)
----read_this.txt(622B)
----Anomaly_using_NN_new_improved.ipynb(67KB)
----Anomaly using NN_new.ipynb(16KB)