כריית מידע -- מבוא ד"ר אבי רוזנפלד.

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Presentation transcript:

כריית מידע -- מבוא ד"ר אבי רוזנפלד

מה לומדים פה... אלגוריתמים של כריית מידע להבין את המשמעות של הפלט (החוקים) של הלמידה איך לייצר את החוקים (WEKA, SQL SERVER) זה לא קורס בבסיסי נתונים (ACCESS) בסיסי נתונים הם חלק, אבל רק חלק מהתהליך

Knowledge Discovery (KDD) Process This is a view from typical database systems and data warehousing communities Data mining plays an essential role in the knowledge discovery process Pattern Evaluation Data Mining Task-relevant Data Selection Data Warehouse Data Cleaning Data Integration Databases

Data Mining in Business Intelligence Increasing potential to support business decisions End User Decision Making Data Presentation Business Analyst Visualization Techniques Data Mining Data Analyst Information Discovery Data Exploration Statistical Summary, Querying, and Reporting Data Preprocessing/Integration, Data Warehouses DBA Data Sources Paper, Files, Web documents, Scientific experiments, Database Systems

תהליך של כריית מידע

שלב הראשון – להבין את הסביבה איזה מידע יש במערכת? האם זה מספיק? האם המידע הסתברותי? האם יש LABEL (מידע אובייקטיבי) Fraud in credit card, fraud in Machon tests מה המחיר לאסוף עוד מידע (Certainty level)

הכנת המידע – איך המידע מאוחסן קובץ EXCEL (הפורמט שאני אוהב) ACCESS SQL, ORACLE, SPSS, MATHLAB וכו'

בניית המודל רוב הקורס– האלגוריתמים בשקפים הבאים...

ניצול החוקים יישום החוקים, הסקת מסקנות, הדרכה וכו' גילוי של מאפיינים חדשים ולמידה מחדש וכו'

האלגוריתמים של כריית מידע Classification – קלסיפיקציה – C4.5 Regression - רגרסיה – polynomial, logistic, SVM Clustering – מיקבוץ – k-NN, k-means Co-occurrence – collaborative filtering Information Retrieval – PageRank Probabilistic models – Bayes, Naïve Bayes

שיטות למידה - Supervised Decision Trees – finding cancer

שיטות למידה - Unsupervised Clustering (k=11)

ההבדל בין כריית מידע ושאילתות בשאלתה אתה בערך יודע מה אתה מחפש: SELECT * FROM CUSTOMERS WHERE AGE > 45 בכריית מידע אתה מחפש משהו ואתה לא יודע מראש מה! SELECT ??? FROM CUSTOMERS WHERE ???

דוגמאות מי מכר הכי הרבה פריטים בתוך החברה (שאילתה) איזה פריטים נמכרו הכי הרבה (שאילתה) האם יש תלות מאיזור המכירה והפריטים שנמכרו שם? (כריית מידע) איך ניתן לנבא כמה נמכור באיזור XXX בעוד שנה? (כריית מידע-- רגרסיה) איך ניתן לנבא אם פריט Y יהיה רווחי (כריית מידע רגרסיה / קלסיפיקציה) איך ניתן לנבא איזה זוגות של פריטים שווה למכור ביחד (כריית מידע clustering, association)