Outliers are data points that significantly deviate from other data points in a data set because ... more Outliers are data points that significantly deviate from other data points in a data set because of different mechanisms or unusual processes. Outlier detection is one of the intensively studied research topics for identification of novelties, frauds, anomalies, deviations or exceptions in addition to its use for data cleansing in data science. In this study, we propose two novel outlier detection approaches using the typicality degrees which are the partitioning result of unsupervised possibilistic clustering algorithms. The proposed approaches are based on finding the atypical data points below a predefined threshold value, a possibilistic level for evaluating a point as an outlier. The experiments on the synthetic and real data sets showed that the proposed approaches can be successfully used to detect outliers without considering the structure and distribution of the features in multidimensional data sets.
Cankaya, S., Kayaalp, G.T., Sangun, L., Tahtali, Y. and Akar, M. 2006. A comparative study of est... more Cankaya, S., Kayaalp, G.T., Sangun, L., Tahtali, Y. and Akar, M. 2006. A comparative study of estimation methods for parameters in multiple linear regression model. J. Appl. Anim. Res., 29: 43–47.This paper investigated least squares method, non-parametric method and robust regression methods to predict the parameters of multiple regression models. To evaluate these methods, measurements of body weight, total length
Outliers are data points that significantly deviate from other data points in a data set because ... more Outliers are data points that significantly deviate from other data points in a data set because of different mechanisms or unusual processes. Outlier detection is one of the intensively studied research topics for identification of novelties, frauds, anomalies, deviations or exceptions in addition to its use for data cleansing in data science. In this study, we propose two novel outlier detection approaches using the typicality degrees which are the partitioning result of unsupervised possibilistic clustering algorithms. The proposed approaches are based on finding the atypical data points below a predefined threshold value, a possibilistic level for evaluating a point as an outlier. The experiments on the synthetic and real data sets showed that the proposed approaches can be successfully used to detect outliers without considering the structure and distribution of the features in multidimensional data sets.
An in vivo experiment was conducted to determine the effect of dietary inclusion of dry Caper (Ca... more An in vivo experiment was conducted to determine the effect of dietary inclusion of dry Caper (Capparis spinosa) leaf powder (DCL) on egg production and egg quality of laying hens at the beginning of the laying period. Four groups of commercial hens (ATAK-S) were fed with diets containing 0, 5, 10 and 15 g DCL/kg. The results demonstrated that dietary DCL had no effect on feed intake, feed efficiency, egg mass (EM) and egg production parameters (P>0.05). Hen-day egg production (HDP) value of the groups was 69.52%, 64.97%, 68.02% and 71.72% respectively. Trolox equivalent antioxidant capacity (TEAC), ferric reducing antioxidant power (FRAP) and total phenolics amount of DCL were 51.06±2.300 mmol trolox/kg, 50.10±3.488 mmol TEAC/kg and 2.78±0.050 g gallic acid equivalents (GAE)/kg respectively. Based on the results from the current study, the dietary DCL with levels up to 15 g/kg neither reduced productivity performance traits nor improved egg quality characteristics.
Turkish Journal of Agriculture - Food Science and Technology, 2020
Bu araştırmada Romanov kuzularının vücut özelliklerinin gelişiminin tanımlanması amacı ile 50 Rom... more Bu araştırmada Romanov kuzularının vücut özelliklerinin gelişiminin tanımlanması amacı ile 50 Romanov kuzusunun doğumdan itibaren 180. yaş gününe kadar olan büyüme döneminde her 15 günde bir canlı ağırlık, vücut uzunluğu, cidago yüksekliği özelliklerine ilişkin kayıtlar alınmış ve elde edilen veriler ile doğrusal modellerden Linear, Kuadratik ve Kübik model, doğrusal olmayan modellerden Gompertz ve Lojistik modelleri kullanılarak büyüme eğrilerine ait parametreler hesaplanmıştır. Büyüme eğrileri içinde en iyi uyumu gösteren modelin belirlenmesinde belirtme katsayısı (R2), hata kareler ortalaması (HKO) ve ortalama mutlak sapma (OMS) değerlerinden yararlanılmıştır. Elde edilen sonuçlara göre en yüksek R2 değeri ile en düşük HKO değerleri sırası ile canlı ağırlıkta 0,992-0,591, cidago yüksekliğinde 0,993-0,441, vücut uzunluğunda 0,986-1,164 olarak tespit edilmiştir. Ele alınan bütün vücut özelliklerinde en yüksek R2 değeri kübik modelden elde edilmiştir. Büyüme eğrisi modellerine ait p...
Kafkas Universitesi Veteriner Fakultesi Dergisi, 2012
In this study, canonical correlation analysis was applied to estimate the relationship between si... more In this study, canonical correlation analysis was applied to estimate the relationship between six different morphologic traits (X set -birth weight (BW), body length (BL), height at withers (HW), chest depth (CD), chest width (CW) and chest girth (CG)) measured at birth and the morphological traits measured at weaning time (Y set -weaning weight (WW), body length (BL_W), height at withers (HW_W), chest depth (CD_W), chest width (CW_W) and chest girth (CG_W)) measured from 121 Karayaka lambs, raised at Gaziosmanpasa University. First of estimated six different canonical correlation coefficients (CCC) (r=0.668) between the pairs of canonical variables were found significant (P<0.05). The results of canonical correlation analysis indicated that height at withers, chest girth and birth weight had largest contribution for the explanatory capacity of canonical variables estimated from the morphologic traits of Karayaka lambs at the birth when compared with other body measurements. Height withers and chest girth had largest contribution for the explanatory capacity of canonical variables estimated from the morphological traits of the lambs at the weaning time when compared with other body measurements. As results of this study showed that height at withers, body weight and chest girth measured at birth can be used as early selection criteria for genetic improvement in Karayaka lambs.
Turkish Journal of Agriculture: Food Science and Technology, Feb 26, 2020
In this study, principal component analysis has been applied on data comprising of 6675 gene and ... more In this study, principal component analysis has been applied on data comprising of 6675 gene and 20 sequence collected by using cDNA microarray technology from livers of mice used in toxicology studies in certain time periods. Forming of gene groups from similar expression profiles and description of related genes which are implemented by similar component loads among the groups have been explained by using this cDNA technology. Besides that, interpretation and decomposition of factors (components) from correlation matrix which belongs to same data group have been explained. Some of the methods developed for minimizing the data set to fewer components which can explain the whole data structure have been evaluated. According to methods, if we assume that the first 9 eigen values are enough to describe the whole variance, then in this case, it is thought that it is good enough to describe the whole variance by using 9 eigen values with a variance loss of 20,79% instead of describing the whole variance by using 20 eigen values.
The aim of this paper was to describe the effects of calf sex, birth month and type on birth weig... more The aim of this paper was to describe the effects of calf sex, birth month and type on birth weight using Regression Tree (RT) analysis. For this purpose, 894 Holstein calves data raised in Polatlı State Farm were analyzed. The birth weight of calves averaged 38.478 ± 2.487 kg of total calves born, 95.5 % were single born. Twin born calves weights were lower (35.125 ± 1.652 kg) than single born (38.635±2.408 kg). Male calves were significantly (P<0.05) heavier than females by 1.28 kg. The mean birth weight of twin calves was 3.58 kg lower than that of single. Effects of calving month, sex of calf, birth type on birth weight were all significant (P<0.05).
Turkish Journal of Agriculture: Food Science and Technology, 2020
The research was carried out in a 3-floor cage system in the research farm of Tokat Gaziosmanpasa... more The research was carried out in a 3-floor cage system in the research farm of Tokat Gaziosmanpasa University. 6 chickens were placed in each cage compartment and 5 repetitions were created on each floor. Existing eggs were collected at 9:00 - 13:00 and 16:00 from a total of 90 Atak-S chickens between 24-42 weeks. A total of 1442 eggs were obtained from 90 chickens. To determine the relationship between cage position and laying time, correspondence analysis was applied. SPSS package program was used to analyze the data. According to the results, it was found statistically significant that chickens on different floors lay eggs at different times. According to the results of the correspondence analysis, the first dimension explanation power was 99.7% and the explanation power in the second dimension was 0.3%. When the inertia in terms of lattice layers in the first dimension was examined, it was determined that the explanation power of the first floor was 65.4%, and in the second dimen...
Kafkas Universitesi Veteriner Fakultesi Dergisi, 2020
This study investigates the modelling of the individual growth curves of Romanov lambs using diff... more This study investigates the modelling of the individual growth curves of Romanov lambs using different equations and the data on the increase in live weight and selects the best model. For this purpose, the live weights of Romanov lambs that were brought to Gürçeşme Village, Niksar, Turkey, from Nikopol, Russia, were recorded from birth to day 180. In the study, the Cubic Spline, Logistic, Gompertz and Richard models were used. For the study, individual growth curves of a total of 278 (178 females, 100 males) lambs were modeled. For the selection of the best model, adjusted determination coefficient (R 2 adj.), mean square error (MSE), Akaike information criteria (AIC) and Durbin-Watson (DW) values were used. In addition, attention was paid to the parameters and standard errors of the models. The results showed that the mean square error for the male lambs varied from 0.295 to 0.995, while it varied from 0.995 to 2.659 for the female lambs; the R 2 adj. values were between 0.971 and 0.997 for the male lambs and 0.969 and 0.993 for the female lambs. The AIC values were between-37.12 and 0.094 for the male lambs and-0.196 and 122.12 for the female lambs. The DW values ranged from 1.86 to 2.44 for the female lambs and from 1.02 to 2.79 for the male lambs. Considering the MSE, R 2 adj., AIC and DW values of the female lambs (0.295±1.195, 0.997±0.002,-37.12±0.001, 2.23±0.49, respectively) and male lambs (0.995±1.021, 0.993±0.001,-122.12±0.05, 2.31±0.19, respectively), the Cubic Spline model was determined to be the best model, while the Richard model was determined to be the worst fitting model both for the female (0.95±5.
Kafkas Universitesi Veteriner Fakultesi Dergisi, 2020
The study investigates the classification of milk quality with support vector machines (SVM) usin... more The study investigates the classification of milk quality with support vector machines (SVM) using the raw milk composition and somatic cell count (SCC) data on buffalos. For this purpose, 11-variable (dry matter, fat-free dry matter, fat (%), protein, lactose, casein, urea, density, acidity, pH, freezing point) on milk composition and SCC of 288 buffalos were used. SVM is a classifier with a high generalization ability that is based on structural risk minimization with a statistical learning system and can be applied to both linear and non-linear data. The classification successes of some kernel functions used in the SVM (polynomial kernel, normalized polynomial kernel and radial basis kernel) were investigated and their classification performances were compared with a multilayer perceptron algorithm. The results showed that the classification successes of polynomial kernel, normalized polynomial kernel and radial basis kernel were 93.06%, 92.36% and 90.97%, respectively, while the classification success of the multilayer perceptron was 81.60%. The comparison of the results with respect to the root mean square error (RMSE) values revealed that the polynomial kernel had the lowest value (0.263), while the multilayer perceptron had the highest value (0.384). According to this criterion, the best classifier was the polynomial kernel function, while the weakest classifier was the multilayer perceptron (0.384). Considering the receiver operating characteristic (ROC) area values, with respect to the closeness to 1 criterion, normalized polynomial kernel was the best function, while the multilayer perceptron function was the weakest function. The separate evaluation of the precision, sensitivity and F-measure values showed that the polynomial kernel was the most successful function, while the multilayer perceptron was the weakest function.
Turkish Journal of Agriculture - Food Science and Technology, 2020
The aim of this study is to compare the least squares (LS) method that lost its function in the c... more The aim of this study is to compare the least squares (LS) method that lost its function in the case of multicollinearity in regression methods with Ridge Regression (RR) and Principal Components Regression (PCR) which are bias estimators. For this aim, the effect of some body measurements on body weight (BW), body length (BL), height at withers (HW), height at rump (HR), chest depth (CD), chest girth (CG) and chest width (CW) obtained from 59 Saanen kids at weaning period raised at Research Farm of Tokat Gaziosmanpaşa University. Determination coefficient (R2) and mean square error (MSE) values were used to evaluate the estimation performance of the methods. The multicollinearity between height at withers (HW) and height at rump (HR) which were used to estimate body weight was eliminated by using RR and PCR. When R2 and HKO values of the examined methods are compared; It has been shown that RR method have better results of live weight of Saanen goats.
Bu çalışma kafes katının yumurtacı hibritlerin performans özelliklerine, yumurta kalitesi ve bazı... more Bu çalışma kafes katının yumurtacı hibritlerin performans özelliklerine, yumurta kalitesi ve bazı stres parametrelerine etkisini araştırmak amacıyla yapılmıştır. Araştırma üç katlı geleneksel kafes sisteminde 90 yumurtacı hibrit (ATAK-S) üzerinde yürütülmüştür. Deneme 18. haftalık yaşta başlamış 42. haftalık yaşta sonlandırılmıştır. Deneme başlangıcında yerleştirilen hibritlerin canlı ağırlıklarının birbirine yakın olmasına dikkat edilmiştir. Kat 1, kat 2 ve kat 3 te %5 verim yaşı sırasıyla 151, 146 ve 156 gün; %50 verim yaşı ise sırasıyla 162,40; 158,60 ve 161,80 gün; %5 verim canlı ağırlığı sırasıyla 1597,83; 1460,53 ve 1599,17 g (P<0,01); %50 verim canlı ağırlığı ise sırasıyla 1708,70; 1666,37 ve 1671,69 g (P>0,05) olarak tespit edilmiştir. Kafes katının yumurtacı hibritlerin 30 ve 42. hafta canlı ağırlık, yemden yararlanma oranına, tonik immobilite süresine, yumurta ağırlığına, yumurta verimine, yumurta iç ve dış kalite özelliklerine etkisi önemsiz bulunmuştur (P>0,05)....
Outliers are data points that significantly deviate from other data points in a data set because ... more Outliers are data points that significantly deviate from other data points in a data set because of different mechanisms or unusual processes. Outlier detection is one of the intensively studied research topics for identification of novelties, frauds, anomalies, deviations or exceptions in addition to its use for data cleansing in data science. In this study, we propose two novel outlier detection approaches using the typicality degrees which are the partitioning result of unsupervised possibilistic clustering algorithms. The proposed approaches are based on finding the atypical data points below a predefined threshold value, a possibilistic level for evaluating a point as an outlier. The experiments on the synthetic and real data sets showed that the proposed approaches can be successfully used to detect outliers without considering the structure and distribution of the features in multidimensional data sets.
Cankaya, S., Kayaalp, G.T., Sangun, L., Tahtali, Y. and Akar, M. 2006. A comparative study of est... more Cankaya, S., Kayaalp, G.T., Sangun, L., Tahtali, Y. and Akar, M. 2006. A comparative study of estimation methods for parameters in multiple linear regression model. J. Appl. Anim. Res., 29: 43–47.This paper investigated least squares method, non-parametric method and robust regression methods to predict the parameters of multiple regression models. To evaluate these methods, measurements of body weight, total length
Outliers are data points that significantly deviate from other data points in a data set because ... more Outliers are data points that significantly deviate from other data points in a data set because of different mechanisms or unusual processes. Outlier detection is one of the intensively studied research topics for identification of novelties, frauds, anomalies, deviations or exceptions in addition to its use for data cleansing in data science. In this study, we propose two novel outlier detection approaches using the typicality degrees which are the partitioning result of unsupervised possibilistic clustering algorithms. The proposed approaches are based on finding the atypical data points below a predefined threshold value, a possibilistic level for evaluating a point as an outlier. The experiments on the synthetic and real data sets showed that the proposed approaches can be successfully used to detect outliers without considering the structure and distribution of the features in multidimensional data sets.
An in vivo experiment was conducted to determine the effect of dietary inclusion of dry Caper (Ca... more An in vivo experiment was conducted to determine the effect of dietary inclusion of dry Caper (Capparis spinosa) leaf powder (DCL) on egg production and egg quality of laying hens at the beginning of the laying period. Four groups of commercial hens (ATAK-S) were fed with diets containing 0, 5, 10 and 15 g DCL/kg. The results demonstrated that dietary DCL had no effect on feed intake, feed efficiency, egg mass (EM) and egg production parameters (P>0.05). Hen-day egg production (HDP) value of the groups was 69.52%, 64.97%, 68.02% and 71.72% respectively. Trolox equivalent antioxidant capacity (TEAC), ferric reducing antioxidant power (FRAP) and total phenolics amount of DCL were 51.06±2.300 mmol trolox/kg, 50.10±3.488 mmol TEAC/kg and 2.78±0.050 g gallic acid equivalents (GAE)/kg respectively. Based on the results from the current study, the dietary DCL with levels up to 15 g/kg neither reduced productivity performance traits nor improved egg quality characteristics.
Turkish Journal of Agriculture - Food Science and Technology, 2020
Bu araştırmada Romanov kuzularının vücut özelliklerinin gelişiminin tanımlanması amacı ile 50 Rom... more Bu araştırmada Romanov kuzularının vücut özelliklerinin gelişiminin tanımlanması amacı ile 50 Romanov kuzusunun doğumdan itibaren 180. yaş gününe kadar olan büyüme döneminde her 15 günde bir canlı ağırlık, vücut uzunluğu, cidago yüksekliği özelliklerine ilişkin kayıtlar alınmış ve elde edilen veriler ile doğrusal modellerden Linear, Kuadratik ve Kübik model, doğrusal olmayan modellerden Gompertz ve Lojistik modelleri kullanılarak büyüme eğrilerine ait parametreler hesaplanmıştır. Büyüme eğrileri içinde en iyi uyumu gösteren modelin belirlenmesinde belirtme katsayısı (R2), hata kareler ortalaması (HKO) ve ortalama mutlak sapma (OMS) değerlerinden yararlanılmıştır. Elde edilen sonuçlara göre en yüksek R2 değeri ile en düşük HKO değerleri sırası ile canlı ağırlıkta 0,992-0,591, cidago yüksekliğinde 0,993-0,441, vücut uzunluğunda 0,986-1,164 olarak tespit edilmiştir. Ele alınan bütün vücut özelliklerinde en yüksek R2 değeri kübik modelden elde edilmiştir. Büyüme eğrisi modellerine ait p...
Kafkas Universitesi Veteriner Fakultesi Dergisi, 2012
In this study, canonical correlation analysis was applied to estimate the relationship between si... more In this study, canonical correlation analysis was applied to estimate the relationship between six different morphologic traits (X set -birth weight (BW), body length (BL), height at withers (HW), chest depth (CD), chest width (CW) and chest girth (CG)) measured at birth and the morphological traits measured at weaning time (Y set -weaning weight (WW), body length (BL_W), height at withers (HW_W), chest depth (CD_W), chest width (CW_W) and chest girth (CG_W)) measured from 121 Karayaka lambs, raised at Gaziosmanpasa University. First of estimated six different canonical correlation coefficients (CCC) (r=0.668) between the pairs of canonical variables were found significant (P<0.05). The results of canonical correlation analysis indicated that height at withers, chest girth and birth weight had largest contribution for the explanatory capacity of canonical variables estimated from the morphologic traits of Karayaka lambs at the birth when compared with other body measurements. Height withers and chest girth had largest contribution for the explanatory capacity of canonical variables estimated from the morphological traits of the lambs at the weaning time when compared with other body measurements. As results of this study showed that height at withers, body weight and chest girth measured at birth can be used as early selection criteria for genetic improvement in Karayaka lambs.
Turkish Journal of Agriculture: Food Science and Technology, Feb 26, 2020
In this study, principal component analysis has been applied on data comprising of 6675 gene and ... more In this study, principal component analysis has been applied on data comprising of 6675 gene and 20 sequence collected by using cDNA microarray technology from livers of mice used in toxicology studies in certain time periods. Forming of gene groups from similar expression profiles and description of related genes which are implemented by similar component loads among the groups have been explained by using this cDNA technology. Besides that, interpretation and decomposition of factors (components) from correlation matrix which belongs to same data group have been explained. Some of the methods developed for minimizing the data set to fewer components which can explain the whole data structure have been evaluated. According to methods, if we assume that the first 9 eigen values are enough to describe the whole variance, then in this case, it is thought that it is good enough to describe the whole variance by using 9 eigen values with a variance loss of 20,79% instead of describing the whole variance by using 20 eigen values.
The aim of this paper was to describe the effects of calf sex, birth month and type on birth weig... more The aim of this paper was to describe the effects of calf sex, birth month and type on birth weight using Regression Tree (RT) analysis. For this purpose, 894 Holstein calves data raised in Polatlı State Farm were analyzed. The birth weight of calves averaged 38.478 ± 2.487 kg of total calves born, 95.5 % were single born. Twin born calves weights were lower (35.125 ± 1.652 kg) than single born (38.635±2.408 kg). Male calves were significantly (P<0.05) heavier than females by 1.28 kg. The mean birth weight of twin calves was 3.58 kg lower than that of single. Effects of calving month, sex of calf, birth type on birth weight were all significant (P<0.05).
Turkish Journal of Agriculture: Food Science and Technology, 2020
The research was carried out in a 3-floor cage system in the research farm of Tokat Gaziosmanpasa... more The research was carried out in a 3-floor cage system in the research farm of Tokat Gaziosmanpasa University. 6 chickens were placed in each cage compartment and 5 repetitions were created on each floor. Existing eggs were collected at 9:00 - 13:00 and 16:00 from a total of 90 Atak-S chickens between 24-42 weeks. A total of 1442 eggs were obtained from 90 chickens. To determine the relationship between cage position and laying time, correspondence analysis was applied. SPSS package program was used to analyze the data. According to the results, it was found statistically significant that chickens on different floors lay eggs at different times. According to the results of the correspondence analysis, the first dimension explanation power was 99.7% and the explanation power in the second dimension was 0.3%. When the inertia in terms of lattice layers in the first dimension was examined, it was determined that the explanation power of the first floor was 65.4%, and in the second dimen...
Kafkas Universitesi Veteriner Fakultesi Dergisi, 2020
This study investigates the modelling of the individual growth curves of Romanov lambs using diff... more This study investigates the modelling of the individual growth curves of Romanov lambs using different equations and the data on the increase in live weight and selects the best model. For this purpose, the live weights of Romanov lambs that were brought to Gürçeşme Village, Niksar, Turkey, from Nikopol, Russia, were recorded from birth to day 180. In the study, the Cubic Spline, Logistic, Gompertz and Richard models were used. For the study, individual growth curves of a total of 278 (178 females, 100 males) lambs were modeled. For the selection of the best model, adjusted determination coefficient (R 2 adj.), mean square error (MSE), Akaike information criteria (AIC) and Durbin-Watson (DW) values were used. In addition, attention was paid to the parameters and standard errors of the models. The results showed that the mean square error for the male lambs varied from 0.295 to 0.995, while it varied from 0.995 to 2.659 for the female lambs; the R 2 adj. values were between 0.971 and 0.997 for the male lambs and 0.969 and 0.993 for the female lambs. The AIC values were between-37.12 and 0.094 for the male lambs and-0.196 and 122.12 for the female lambs. The DW values ranged from 1.86 to 2.44 for the female lambs and from 1.02 to 2.79 for the male lambs. Considering the MSE, R 2 adj., AIC and DW values of the female lambs (0.295±1.195, 0.997±0.002,-37.12±0.001, 2.23±0.49, respectively) and male lambs (0.995±1.021, 0.993±0.001,-122.12±0.05, 2.31±0.19, respectively), the Cubic Spline model was determined to be the best model, while the Richard model was determined to be the worst fitting model both for the female (0.95±5.
Kafkas Universitesi Veteriner Fakultesi Dergisi, 2020
The study investigates the classification of milk quality with support vector machines (SVM) usin... more The study investigates the classification of milk quality with support vector machines (SVM) using the raw milk composition and somatic cell count (SCC) data on buffalos. For this purpose, 11-variable (dry matter, fat-free dry matter, fat (%), protein, lactose, casein, urea, density, acidity, pH, freezing point) on milk composition and SCC of 288 buffalos were used. SVM is a classifier with a high generalization ability that is based on structural risk minimization with a statistical learning system and can be applied to both linear and non-linear data. The classification successes of some kernel functions used in the SVM (polynomial kernel, normalized polynomial kernel and radial basis kernel) were investigated and their classification performances were compared with a multilayer perceptron algorithm. The results showed that the classification successes of polynomial kernel, normalized polynomial kernel and radial basis kernel were 93.06%, 92.36% and 90.97%, respectively, while the classification success of the multilayer perceptron was 81.60%. The comparison of the results with respect to the root mean square error (RMSE) values revealed that the polynomial kernel had the lowest value (0.263), while the multilayer perceptron had the highest value (0.384). According to this criterion, the best classifier was the polynomial kernel function, while the weakest classifier was the multilayer perceptron (0.384). Considering the receiver operating characteristic (ROC) area values, with respect to the closeness to 1 criterion, normalized polynomial kernel was the best function, while the multilayer perceptron function was the weakest function. The separate evaluation of the precision, sensitivity and F-measure values showed that the polynomial kernel was the most successful function, while the multilayer perceptron was the weakest function.
Turkish Journal of Agriculture - Food Science and Technology, 2020
The aim of this study is to compare the least squares (LS) method that lost its function in the c... more The aim of this study is to compare the least squares (LS) method that lost its function in the case of multicollinearity in regression methods with Ridge Regression (RR) and Principal Components Regression (PCR) which are bias estimators. For this aim, the effect of some body measurements on body weight (BW), body length (BL), height at withers (HW), height at rump (HR), chest depth (CD), chest girth (CG) and chest width (CW) obtained from 59 Saanen kids at weaning period raised at Research Farm of Tokat Gaziosmanpaşa University. Determination coefficient (R2) and mean square error (MSE) values were used to evaluate the estimation performance of the methods. The multicollinearity between height at withers (HW) and height at rump (HR) which were used to estimate body weight was eliminated by using RR and PCR. When R2 and HKO values of the examined methods are compared; It has been shown that RR method have better results of live weight of Saanen goats.
Bu çalışma kafes katının yumurtacı hibritlerin performans özelliklerine, yumurta kalitesi ve bazı... more Bu çalışma kafes katının yumurtacı hibritlerin performans özelliklerine, yumurta kalitesi ve bazı stres parametrelerine etkisini araştırmak amacıyla yapılmıştır. Araştırma üç katlı geleneksel kafes sisteminde 90 yumurtacı hibrit (ATAK-S) üzerinde yürütülmüştür. Deneme 18. haftalık yaşta başlamış 42. haftalık yaşta sonlandırılmıştır. Deneme başlangıcında yerleştirilen hibritlerin canlı ağırlıklarının birbirine yakın olmasına dikkat edilmiştir. Kat 1, kat 2 ve kat 3 te %5 verim yaşı sırasıyla 151, 146 ve 156 gün; %50 verim yaşı ise sırasıyla 162,40; 158,60 ve 161,80 gün; %5 verim canlı ağırlığı sırasıyla 1597,83; 1460,53 ve 1599,17 g (P<0,01); %50 verim canlı ağırlığı ise sırasıyla 1708,70; 1666,37 ve 1671,69 g (P>0,05) olarak tespit edilmiştir. Kafes katının yumurtacı hibritlerin 30 ve 42. hafta canlı ağırlık, yemden yararlanma oranına, tonik immobilite süresine, yumurta ağırlığına, yumurta verimine, yumurta iç ve dış kalite özelliklerine etkisi önemsiz bulunmuştur (P>0,05)....
Uploads
Papers by Yalcin Tahtali