Each passing day data is getting multiplied. It is difficult to extract useful information from such big data. Data Mining is used to extract useful information. Data mining is used in majorly all fields like healthcare, marketing, social media platforms and so on. In this paper, data is loaded and preprocessed by dealing with some missing values. The dataset used is of Airbnb, the platform used for lodging and tourism industry. Analyzing the data by plotting correlation using spearman method. Further, applying PCA and Support Vector Machine classification technique on the dataset. There are various applications of SVM, it is used in face-detection, text and hypertext categorization, classification of images, bioinformatics and so on. SVM has high dimensional input space, sparse document vectors and regularization parameters therefore it is appropriate to use SVM. Cross-validation gives more accurate result. The dataset is divided into folds. The end product is the test set which is similar to full dataset. Confusion matrix is evaluated, grid approach is followed for building the matrix at various seeds and kernels (RBF, Polynomial). The aim of this research is to see which is the best kernel for the dataset.

BACKGROUND:Nephrotic syndrome (NS) results in proteinuria of more than 3.5 g protein per day and is characterized by edema,hyperlipidemia,hypoproteinemia and other metabolic disorders.Prevalence of UTI in nephrotic syndrome is high.It precipitates relapse and delays remission. AIMS AND OBJECTIVES:The aim of this retrospective study is to analyze the incidence of UTI,its Predisposing factors along with its bacterial and fungal etiologies in patients with NS and antibiotic sensitivity pattern in nephrotic children with UTI. METHODS: This retrospective study was carried out in a tertiary care, CIVIL HOSPITAL,AHMEDABAD between July 2018 and July 2019 among the admitted cases of nephrotic children under 12 years of age. Examinations for microscopy and cultures of urine, sputum, throat swab, blood and fluid were also carried out in the children,along with routine examination,if found necessary. Urinary specimens were collected by clean catch method following careful preparation of urethral orifices. The specimens were immediately inoculated on culture media. Identification of organisms and antibiotic sensitivity 1 susceptibility testing was performed according to CLSI guidelines 2010 by Kirby –Bauer disc diffusion method. RESULTS: Total 41 nephrotic children were enrolled.Incidence of UTI was fairly high in nephrotic syndrome,especially in frequent relapse (48.48%). Kleibsella pneumonia (45.5%) was the most common organism, followed by E.coli (24.24%),responsible for UTI in both first episode and frequent relapse of nephrotic syndrome in the following study. CONCLUSION: As per the study, common isolates of UTI in nephrotic syndrome have developed resistance to commonly used oral or parenteral drugs.In my study,it is observed that colistin was the most sensitive parenteral drug for all isolates followed by Meropenem and aminoglycoside.